# Releases

## How to cite

[![](https://joss.theoj.org/papers/10.21105/joss.06734/status.svg)](https://doi.org/10.21105/joss.06734)

REHO has been published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.06734). If you use REHO in your research, please cite it using the following reference:

**APA**

```bash
Lepour et al., (2024). REHO: A Decision Support Tool for Renewable Energy Communities. Journal of Open Source Software, 9(103), 6734, https://doi.org/10.21105/joss.06734
```

**BibTeX**

```bash
@article{Lepour2024, doi = {10.21105/joss.06734}, url = {https://doi.org/10.21105/joss.06734}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {103}, pages = {6734}, author = {Dorsan Lepour and Joseph Loustau and Cédric Terrier and François Maréchal}, title = {REHO: A Decision Support Tool for Renewable Energy Communities}, journal = {Journal of Open Source Software} }
```


## License

Copyright (C) \<2021-2026\> \<Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland\>

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

## Code versions

REHO is as an open-source and collaborative Python library.
Its GitHub repository (https://github.com/IPESE/REHO) is freely accessible and contains the entire history of the
software since it was made available to the public in August 2023.


## Applications using REHO

:::{dropdown} {bdg-primary}`Web-app` REHO-fm, Fayt, Lepour & Loustau 2023
:icon: gear

[REHO-fm](https://reho.epfl.ch/) is a web application that compares energy scenarios for the entire Swiss building stock.
The application is based on the REHO open-source optimization model and its input data comes from the [QBuildings](https://qbuildings.epfl.ch/) database.
:::

:::{dropdown} {bdg-primary}`Web-app` APECC, Lepour 2024
:icon: gear

[APECC](https://ipese-web.epfl.ch/lepour/apecc/) helps to explore innovative energy solutions for the canton of Geneva. Combining interactive maps and data visualization, it offers an analysis of energy systems from technical, economic and environmental perspectives. It aims to support citizens, municipalities and energy suppliers in the energy transition and in reducing the carbon footprint of the building stock.

It has been developed as part of a collaboration between the Industrial Process and Energy Systems Engineering laboratory (IPESE, EPFL) and the Services Industriels de Genève (SIG).
:::

:::{dropdown} {bdg-primary}`Web-app` SIG - VarÉlec, Lepour & Loustau 2022
:icon: gear

[SIG - VarÉlec](https://dorsanlepour.shinyapps.io/SIG_visualiser/) is an interactive tool that allows analyzing the impact of the tariff structure set by the electricity utility on the optimal choice for the end-user's energy system.

A set of results is pre-generated by REHO, based on the minimization of the total costs (TOTEX) of a residential building located in Geneva.
:::


## Related work

### Model foundations

The first developments associated to the model are related to Paul Stadler's thesis,
which presents the buildings modeling framework and serves as a basis for the AMPL model.

:::{dropdown} {bdg-primary}`PhD thesis` Model-based sizing of building energy systems with renewable sources, Stadler 2019 {cite}`stadlerModelbasedSizingBuilding2019`
:icon: mortar-board

**Abstract**

The built environment currently represents the largest sector in terms of final energy consumption, both in Switzerland and the European Union. Most of the associated energy services, such as space heating and potable hot water preparation, are mainly satisfied by the combustion of fossil fuels, typically oil and natural gas. Hence, within the current context of national energy transition towards a sustainable and environment-friendly service provision, the building sector is facing a major challenge to integrate both efficient conversion technologies and additional renewable energy sources. Nevertheless, an increasing penetration of the latter is not a straightforward task; solar power, a typical resource available in urban areas, is indeed intrinsically volatile which renders a full exploitation of the generated electricity highly compelling. The implementation of advanced mathematical modelling methods during the phases of both design and operation represent a promising cornerstone to successfully reach the objectives targeted by the transition program.

Using a model-based approach, the following thesis therefore attempts in contributing to the latter challenge through three main targets. The first aims at the development of a holistic and modular modelling framework to optimally size and operate building energy systems. In order to provide multiple good trade-off system solutions to the various stakeholders, the proposed method relies on an epsilon-constraint multi-objective optimisation techniques and ad hoc defined key performance indicators. A systematic implementation of the thus developed framework finally allows the large-scale analysis of modern and efficient building energy systems, both in view of future market opportunities and national environmental targets.

The second topic focuses on the study of multi-building energy systems and analyses the potential benefits from involving multiple end-users during the sizing process. Through an extended system scope, potential synergies of neighbouring building types arise and hence, the initial modelling framework is further developed accordingly. Additional shared unit technologies, such as inter-day storage and heating networks become interesting elements for buildings interaction and therefore are also integrated in the modelling framework. Finally, the third target addresses the quantification of potential ancillary services performed by different energy system configurations to power network operators. Using a representative set of flexibility request profiles, the modelling framework is systematically solved to assess the associated temporal load shifting potential in comparison to standard electrical battery energy storage systems.
:::

The formulation of the district-scale problem is the contribution of Luise Middelhauve's thesis,
which applies the Dantzig-Wolfe decomposition algorithm to bypass the computation effort associated with numerous interacting buildings.
The thesis also focuses in particular on the role of integrating photovoltaic panels into neighbourhoods.

:::{dropdown} {bdg-primary}`PhD thesis` On the role of districts as renewable energy hubs, Middelhauve 2022 {cite}`middelhauveRoleDistrictsRenewable2022`
:icon: mortar-board

**Abstract**

Although inevitable, the process of transforming urban areas into sustainable living environments presents many challenges. The decentralization of the energy system, the interconnection of multiple energy carriers, and the need to account for conflicting interests renders it a complex task. As key stakeholders, authorities often lack appropriate decision tools to frame and encourage the transition and to monitor the impact of implemented policies.

This work aims to provide useful insights into the role of districts as renewable energy hubs by showing requirements and highlighting constraints, leading to an increase in renewable energy penetration. The benefits and trade-offs between centralized and decentralized renewable energy hubs are emphasized to contribute to the ongoing discussion regarding sustainable urban planning.

Mathematical programming is used to build a multi-objective optimization platform that integrates several renewable technologies with a special focus on solar integration. Specifically, this approach includes the role of the orientation of PV panels and the use of facades, including mounting partly shadowed PV panels and receiving solar heat gain. A decomposition algorithm (Dantzig-Wolfe) is used to bypass the computation effort associated with centralized energy hubs at the district scale.

The results highlight that a low-emission electrical grid mix has a high impact on sustainable design of renewable energy hubs at the building scale and led to less independent system configurations. Optimally integrating of solar systems had a significant impact on their interaction with the electrical grid: rotating the panels 20° westwards reduced the grid exchange peak by 50% while increasing cost by only 8.3%. Moreover, the studied district could achieve carbon neutrality based on PV energy alone, whereas self-sufficiency is more ambitious that confirmed the importance of storage systems: even with 100% round-trip efficiency of storage systems, the required ratio of area covered in PV modules to the ERA was 0.44 and 16% of available facades were needed to be covered with PV modules. However, energy demand reduction through thermal renovation would allow self-sufficiency with half of the PV and storage capacity. Overall, this work demonstrates that moving from a decentralized to coordinated and centralized design strategy allows a higher electrification rate and an increased integration of renewable energy in the district for the same total expenses. The centralized investment strategy differed most from the decentralized strategy for PV panels; using the centralized strategy, a wide range of PV installation on less-optimal surfaces became economically interesting. The most economically convenient solution to overcome transformer limitations were district storage for peak shaving and photovoltaic curtailment. The cost increase were around 600 CHF per kWyr annual capacity shortage, regardless of the considered district energy system.
:::

These previous developments were subsequently merged into a single unified optimization framework, constituting the creation of REHO and its deployment as an open-source library.
The framework was then consolidated and progressively extended with: automatic connection to GIS database for structured data input retrieval, new energy layers and technologies, deployment of
units at both building and district scale, and the implementation of the actors model extension for multi-stakeholder energy community optimization.

:::{dropdown} {bdg-primary}`PhD thesis` Renewable energy communities for the energy transition, Lepour 2026 {cite}`lepourRenewableEnergyCommunities2026`
:icon: mortar-board

**Abstract**

Across Europe and beyond, energy systems are undergoing a double transition: from fossil-based, centralized supply to renewable, distributed infrastructures, and from distant, utility-led decision making to locally grounded investments by heterogeneous actors. This thesis investigates how Renewable Energy Communities (RECs) can become a vehicle for both transitions by coordinating technologies, operations, and costs at the scale of districts and municipalities. The central research question is: how can RECs efficiently support the transformation of local energy systems, and how should expenses and benefits be allocated among stakeholders to ensure technical feasibility, fairness, and economic viability?

Methodologically, the work studies RECs along two complementary axes –technical innovation and economic integration– within a unified, bottom-up modeling framework that shifts the perspective from supplying energy carriers to fulfilling end-use energy services. On the technical axis, the framework evaluates options for building- and district-scale assets, along with efficiency measures, sector coupling, and grid integration strategies, and co-designs capacities and operations to leverage shared infrastructure. On the economic axis, the framework identifies stakeholders and business models, implements internal energy pricing for the community, and constrains actor portfolios to balance affordability for end users and profitability for capital providers.

The manuscript is structured in four steps that progressively assemble the REC concept. Chapter 1 builds a territorial evidence base: it defines energy services, links them to the characterized building stock and local resources in a geographical information system (GIS) database, and clusters districts into archetypes to enable extrapolation. Chapter 2 models buildings as multi-energy hubs via a mixed-integer linear programming (MILP) formulation, generating a comprehensive set of feasible configurations (investments and operational profiles) under diverse contexts, including emerging technologies and flexibility strategies. Chapter 3 extends the hub model to districts through a Dantzig-Wolfe decomposition, quantifying the benefits of pooling prosumers, coordinating decisions, and deploying shared assets (e.g., batteries, centralized heating, smart mobility) under grid constraints. Chapter 4 translates technical configurations into actor-specific cash flows by formalizing internal pricing and business models, thereby bridging design choices with implementable cost allocation and governance. Together, the chapters connect territorial heterogeneity, technology design, coordination mechanisms, and stakeholders alignment.

From the scientific perspective, the thesis contributes: (i) a data-driven clustering framework to typify districts as collections of end users –validated at regional and national scale, enabling large-area REC studies; (ii) advances in building energy-hub design and operation that evaluate emerging technologies, sector coupling, and energy management through flexibility and storage options; (iii) a grid-aware district hub model using decomposition to capture the value of coordination and shared infrastructure; and (iv) an internal pricing and actor-portfolio formulation that operationalizes business models and fairness constraints within RECs.

Practically, the work presented promotes open science by delivering an open-access dataset (QBuildings) and an open-source decision-support tool (REHO) for buildings and districts, applied to the Swiss building stock and validated with utilities. These outputs foster transparent, reproducible research while informing policy and investment decisions for REC deployment at scale.
:::


### Academic contributions

:::{dropdown} {bdg-primary}`Conference` Reducing demand to reduce costs: the system-wide value of energy sufficiency in buildings and mobility, Terrier 2026
:icon: globe

*The 36th European Symposium on Computer Aided Process Engineering (ECOS) - June 28th – July 3rd 2026, Constanta, Romania*

**Abstract**

*(will be published after conference)*
:::

:::{dropdown} {bdg-primary}`Conference` Embedding local energy systems in national models: a decomposition-based coupling of multi-scale energy system, Lepour 2026
:icon: globe

*The 36th European Symposium on Computer Aided Process Engineering (ECOS) - June 28th – July 3rd 2026, Constanta, Romania*

**Abstract**

*(will be published after conference)*
:::

:::{dropdown} {bdg-primary}`Conference` The blur notion of optimal designs in urban areas in high-uncertainty economic contexts, Waeber 2026
:icon: globe

*SITES-AICC conference 2026: Development and Climate Mitigation/Adaptation - May 27-29, 2026 Rome-Frascati, Italy*

**Abstract**

*(will be published after conference)*
:::

:::{dropdown} {bdg-primary}`Conference` Open tools for renewable energy communities: bridging energy modelling and policy, Lepour 2026
:icon: globe

*SITES-AICC conference 2026: Development and Climate Mitigation/Adaptation - May 27-29, 2026 Rome-Frascati, Italy*

**Abstract**

*(will be published after conference)*
:::

:::{dropdown} {bdg-primary}`Journal` Beyond the universal decision maker: renovation policy for decarbonizing energy systems and reducing energy poverty, Terrier 2026 {cite}`terrierBeyondUniversal2026`
:icon: file-badge

**Abstract**

Renovating buildings is necessary for reducing long-term energy use and helping the decarbonization of the building sector. However, conflicting interests and decision-making power between stakeholders, primarily landlords and tenants, keep investment willingness low. Therefore, energy system modeling must transcend centralized decisions and include the modeling of diverse stakeholders. This paper presents a methodology relying on decomposition methods and game theory to integrate multi-scale and multi-actor energy system optimization, spanning from buildings to national energy systems. The results highlight the key role of PV integration within energy communities and local energy markets in ensuring landlords' investment returns while mitigating tenants' energy bills and rent increase. At the national level, most investment in renovation is compensated by decreased investment in grid reinforcement and renewable electricity production. The paper underscores the importance of reducing energy use through renovation and sufficiency measures to lower both infrastructure and energy service expenses.
:::

:::{dropdown} {bdg-primary}`Journal` From servers to services: modeling data centers as heat-active urban energy prosumers, Ravi 2026 {cite}`raviServersServicesModeling2026`
:icon: file-badge

**Abstract**

The rapid expansion of cloud services has significantly increased the global energy footprint of data centers, which now account for approximately 2–3 % of global electricity consumption, a figure projected to rise to somewhere between 10 % and 51 % by 2030. While technological advances such as liquid cooling and high-temperature waste heat streams offer opportunities for improved energy efficiency, the integration of data centers into broader urban energy systems remains limited. This study investigates how data centers can transition from passive energy consumers to active prosumers through advanced heat recovery and flexible demand strategies. In this study, five system-level scenarios are modelled, varying by grid connectivity, renewable energy integration, and workload flexibility. Further, two distinct heat recovery approaches are compared: a legacy strategy that dynamically chooses between direct thermal reuse and electricity generation via an Organic Rankine Cycle (ORC), and an "exergy-aware" strategy that enforces continuous ORC operation and cascades the rejected heat from the condenser into a secondary heat pump. Using a multi-objective Mixed-Integer Linear Programming framework, the study reveals the trade-offs between data self-sufficiency and renewable energy utilization in an urban district case study comprising the EPFL campus in Lausanne. The results show that flexible computing workloads and integration with district heating networks can significantly enhance the buffering potential of data centers for variable renewable energy by up to 28 % in certain cases thereby reducing renewable curtailment, and support more efficient heat-electricity coupling by showing potential to supply up to 40 % of the heat demand of the campus. This work positions data centers as critical enablers of sustainable urban energy systems and offers a transferable modeling framework for their systemic integration.
:::

:::{dropdown} {bdg-primary}`Conference` Solid oxide cells and hydrogen storage to prevent grid congestion, Lepour 2025 {cite}`lepourSolidOxideCells2025`
:icon: globe

*The 35th European Symposium on Computer Aided Process Engineering (ECOS) - July 6-9, 2025, Ghent, Belgium*

**Abstract**

The integration of solid oxide cells and hydrogen storage for building energy systems is investigated. In the context of renewables penetration and electrification of energy services (i.e., deployment of photovoltaics, heat pumps, electric vehicles), the study considers a typical residential building with limited grid capacity for electricity import/export. Five scenarios are investigated, among which a closed-loop system where hydrogen is produced, stored, and locally consumed, and a scenario where hydrogen can also be exported to generate revenues. Results indicate that a reversible solid oxide cell coupled with a hydrogen tank offer a compelling solution as a substitute for electrical storage in the context of grid congestion and PV curtailment. In addition to provide local chemical storage, it makes an efficient use of resources by recovering waste heat generated during cell operation, which is used to partially meet space heating and domestic hot water demands. Another significant aspect of such system is the potential for e-fuel production and hydrogen export.
:::

:::{dropdown} {bdg-primary}`Conference` Potential of reversible solid oxide cells and long-term energy storage in residential areas, Waeber 2025 {cite}`waeberPotentialReversibleSolid2025`
:icon: globe

*The 35th European Symposium on Computer Aided Process Engineering (ECOS) - July 6-9, 2025, Ghent, Belgium*

**Abstract**

This study explores the potential of reversible Solid Oxide Cells (rSOCs) for residential energy storage and decentralized chemical production. rSOCs offer high efficiency, fuel flexibility, and useful heat cogeneration, making them well-suited for balancing renewable energy production throughout the year. This work evaluates the technical and economic feasibility of rSOC systems along with two long-term storage options: Hydrogen (H₂) and Hybrid tank (CH₄/CO₂). The Renewable Energy Hub Optimizer (REHO) is used as an optimization framework considering local resources, multi-energy carriers, and end-use demands in residential areas. A sensitivity analysis is performed to evaluate the benefits of the rSOC integration and enable a fair comparison between the storage options. By assessing TOTEX, storage tank sizes and renewable energy capacity, it also explores the decentralized production of hydrogen as a marketable product for the industry.
:::

:::{dropdown} {bdg-primary}`Conference` Renewable energy communities for the decarbonization of households consumption, Lepour 2025 {cite}`lepourRenewableEnergyCommunities2025`
:icon: globe

*Third International Conference on Action versus Inaction Facing Climate Change (AICC) - June 4-5, 2025, Lausanne, Switzerland*

**Abstract**

This study investigates the "energy cost of living", comprised as the delivery of energy services for residents —including thermal comfort, domestic electricity, mobility, and information and communication technologies (ICT). Coordinated design and operational strategies of energy communities are shown to significantly reduce monthly per capita energy costs from 142.1 CHF for a fossil-based system, to 41.5 CHF for a renewable-integrated system. The environmental footprint is reduced from 2'295 kgCO2-eq/year to negative emissions of -140.4 kgCO2-eq/year, resulting from surplus solar electricity injected into the grid. A further comprehensive evaluation employs the social cost of carbon as a unified economic metric, capturing both financial expenses and environmental impacts of the different renovation scenarios for buildings. Under this evaluation, the conventional fossil-based system incurs a total societal cost of 171.7 CHF per capita per month, whereas the renewable-integrated system achieves a dramatic reduction, lowering the total cost to 39.7 CHF per capita per month. Projected nationally, this translates into potential annual savings of 14.25 billion CHF for Switzerland.
:::

:::{dropdown} {bdg-primary}`Conference` Power to the people: on the role of districts in decentralized energy systems, Chuat 2025 {cite}`chuatPowerPeopleRole2025`
:icon: globe

*Third International Conference on Action versus Inaction Facing Climate Change (AICC) - June 4-5, 2025, Lausanne, Switzerland*

**Abstract**

The transition toward renewable and decentralized energy systems is propelled by the urgent need to address climate concerns and advance sustainable development globally. This transformation requires innovative methods to integrate stochastic renewable sources such as solar and wind power and challenge traditional energy paradigms rooted in centralized and continuous energy production. The present study focuses on the Swiss energy system to explore the optimization of energy planning strategies that incorporate decentralized energy production within a centralized framework. Here, we show that a strategic approach to decentralization can significantly reduce annual system costs by 10% to 1230 CHF per capita and increase self-consumption to 68% of the decentralized PV production, emphasizing the need for a hybrid energy-planning model that balances centralized and decentralized models for enhanced system resilience, efficiency, and cost-effectiveness. This research underscores the strategic importance of diversifying energy sources, enhancing energy storage, improving grid flexibility, and laying a foundational framework for policymaking and strategic planning. It encourages further investigation into climate impacts, technology synergy, and the integration of district heating, aiming to establish a resilient, sustainable, and autonomous energy future.
:::

:::{dropdown} {bdg-primary}`Journal` Internal pricing in integrated energy system design, Granacher 2025 {cite}`granacherInternalPricingIntegrated2025`
:icon: file-badge

**Abstract**

Environmentally sustainable and economically viable process and energy systems are imperative to a successful energy transition. Often, design configurations are derived from a global perspective, in which the individual needs and interests of actors within the system are overlooked. This work proposes an approach for designing a system considering its entire scope and acknowledging the individual actors within the system. System solutions are generated from the perspective of a universal decision-maker who is aware of the whole system, and the obtained solution space is analyzed regarding implications for the individual actors. Thereby, prices of internal exchanges between actors that would allow for the realization of the optimal integrated system solution while granting each actor their economic objectives are derived. The approach is demonstrated in three distinct case studies varying in size: a bio-based industrial site, a renewable energy community, and a national energy system. All case studies yield system configurations allowing the actors to profit from economic benefits emerging from synergies from internal cooperation. Further research must delve into diverse system settings and actor paradigms to enhance the robustness and applicability of the derived insights.
:::

:::{dropdown} {bdg-primary}`Conference` REHO - a comprehensive decision support tool for sustainable energy system planning, Lepour 2024 {cite}`lepourRenewableEnergyHub2024`
:icon: globe

*European Symposium on Computer Aided Process Engineering (Escape) - June 2-6, 2024, Florence, Italy*

**Abstract**

The transition to sustainable energy systems in the face of growing renewable energy adoption and electrification is a complex and critical challenge. The Renewable Energy Hub Optimizer (REHO) emerges as a powerful decision support tool designed to investigate the deployment of energy conversion and storage technologies in this evolving landscape. REHO leverages a Mixed-Integer Linear Programming (MILP) framework combined with a Dantzig-Wolfe decomposition to simultaneously address the optimal design and operation of energy communities, catering to multi-objective considerations across economic, environmental, and efficiency criteria. This paper introduces REHO and highlights its key features and contributions to the field of sustainable energy system planning.
:::

:::{dropdown} {bdg-primary}`Conference` Impact of industrial waste heat recovery on heat and electricity marginal costs in an energy community, Terrier 2024 {cite}`terrierImpactIndustrialWaste2024`
:icon: globe

*European Symposium on Computer Aided Process Engineering (Escape) - June 2-6, 2024, Florence, Italy*

**Abstract**

Sector coupling is seen as one of the keys to improve energy efficiency within urban centers. In this perspective, residential energy system coupled with industrial waste heat recovery via district heating network is a promising solution. However, it also implies the coordination between systems design since a decision taken in one subsystem directly affects the decision-making of other subsystems. The aim of this paper is to demonstrate the sector coupling within an energy community containing an industrial site. The problem is formulated as a renewable energy hub with investment and operation decisions. Each building is modeled individually and the Dantzig-Wolfe decomposition is applied to optimize the district-scale problem. The industrial site is modeled as a heat source with fixed capacity and temperature. The marginal cost analysis demonstrates the spillover effect of waste heat availability on the profitability of PV panels, therefore engendering a self-consumption competition.
:::

:::{dropdown} {bdg-primary}`Journal` Identification of typical district configurations: a two-step global sensitivity analysis framework, Chuat 2024 {cite}`chuatIdentificationTypicalDistrict2024`
:icon: file-badge

**Abstract**

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the imperative of leveraging renewable indigenous energy sources becomes evident. However, as such technologies are integrated into the existing system, it is necessary to shift from the current centralized infrastructure to a decentralized production strategy. This paper presents a method to identify a panel of technological solutions at the district level, intended to reduce complexity for the integration of decentralized models into a national-scale model. The framework's novelty lies in combining a global sensitivity analysis for solution generation with clustering to identify typical configurations. The global sensitivity analysis is performed on a mixed integer linear programming model, which optimally sizes and operates district energy systems. The sensitivity analysis determines the most influential parameters of the model using the Morris method and provides a representative sampling of the solution space by leveraging the Sobol sampling strategy. The latter is then clustered using a density-based algorithm to identify typical solutions. The framework is applied to a suburban and residential Swiss neighborhood. The first outcome of the research is the high sensitivity of the model to energy carrier prices. As a result, Sobol's sampling space separates itself into two system types: those based on a natural gas boiler and those relying on a combination of electrical heaters and heat pumps. For both types, the electricity demand is either fulfilled by PV panels or electricity imports. The identified configurations showcase that the framework successfully generates a panel of solutions composed of various system configurations and operations being representative of the overall solution space.
:::

:::{dropdown} {bdg-primary}`Journal` Power to the people: on the role of districts in decentralized energy systems, Schnidrig 2024 {cite}`schnidrigPowerPeopleRole2024`
:icon: file-badge

**Abstract**

The transition towards renewable and decentralized energy systems is propelled by the urgent need to address climate concerns and advance sustainable development globally. This transformation requires innovative methods to integrate stochastic renewable sources such as solar and wind power and challenging traditional energy paradigms rooted in centralized and continuous energy production. The present study focuses on the Swiss energy system to explore the optimization of energy planning strategies that incorporate decentralized energy production within a centralized framework. Here, we show that a strategic approach to decentralization can significantly reduce annual system costs by 10% to CHF 1230 per capita and increase self-consumption to 68% of the decentralized PV production, emphasizing the need for a hybrid energy-planning model that balances centralized and decentralized models for enhanced system resilience, efficiency, and cost-effectiveness. This research underscores the strategic importance of diversifying energy sources, enhancing energy storage, improving grid flexibility, and laying a foundational framework for policy making and strategic planning. It encourages further investigation into climate impacts, technology synergy, and the integration of district heating, aiming to establish a resilient, sustainable, and autonomous energy future.
:::

:::{dropdown} {bdg-primary}`Journal` From local energy communities towards national energy system: a grid-aware techno-economic analysis, Terrier 2024 {cite}`terrierLocalEnergyCommunities2024`
:icon: file-badge

**Abstract**

Energy communities are key actors in the energy transition since they optimally interconnect renewable energy capacities with the consumers. Despite versatile objectives, they usually aim at improving the self-consumption of renewable electricity within low-voltage grids to maximize revenues. In addition, energy communities are an excellent opportunity to supply renewable electricity to regional and national energy systems. However, effective price signals have to be designed to coordinate the needs of the energy infrastructure with the interests of these local stakeholders. The aim of this paper is to demonstrate the integration of energy communities at the national level with a bottom–up approach. District energy systems with a building scale resolution are modeled in a mixed-integer linear programming problem. The Dantzig–Wolfe decomposition is applied to reduce the computational time. The methodology lies within the framework of a renewable energy hub, characterized by a high share of photovoltaic capacities. Both investments into equipment and its operation are considered. The model is applied on a set of five typical districts and weather locations representative of the Swiss building stock. The extrapolation to the national scale reveals a heterogeneous photovoltaic potential throughout the country. Present electricity tariffs promote a maximal investment into photovoltaic panels in every region, reaching an installed capacity of 67.2 GW and generating 80 TWh per year. Placed in perspective with the optimal PV capacity forecast at 15.4 GW at the national level, coordinated investment between local and national actors is needed to prevent dispensable expenses. An uncoordinated design is expected to increase the total costs for residential energy systems from 12% to 83% and curtails 48% of local renewable electricity.
:::

:::{dropdown} {bdg-primary}`Conference` Clustering and typification of urban districts for energy system modelling, Loustau 2023 {cite}`loustauClusteringTypificationUrban2023`
:icon: globe

*International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS) - June 25-30, 2023, Gran Canaria, Spain*

**Abstract**

The interest in Urban Systems has been growing due to the necessary decarbonisation of city energy systems. Decision tools are developed using mathematical optimisation to enable proper decision-making in the transition process. The concept of energy communities - or district energy hub - is expected to have an impact on the energy system at both regional and national scales. However, the shift towards distributed energy systems complexifies the model due to more integrated subsystems and requires larger spatial boundaries to increase self-consumption and decrease grid stresses. The computational power required to model and optimise such systems is to rise drastically. This work proposes to curtail the large computing needs by typifying the districts of a city, using clustering techniques. Accordingly clustered districts can be optimised by solving a typical district from the group and scaling its solution to the others. The clustering features considered are the districts energetic characteristics: the energy demands on one side, and the endogenous resources on the other. Data are normalised and a principal component analysis is conducted. Two clustering algorithms are investigated: a centroid-based (Kmedoids) and a density-based (GaussianMixture). The ideal number of clusters is determined by maximising the intra-cluster similarity and minimising the inter-cluster similarity, and the final clustering stability is evaluated through the Rand Index. The method is applied on the case study of a typical European urban area and the two algorithms lead to two distinct typification. The clusterings are used to run an energy hub optimisation for the whole region and the results are compared to the one obtained without archetypes for validation. The results between the two approaches show no significant differences while a considerable computing time reduction is achieved.
:::

:::{dropdown} {bdg-primary}`Journal` Electrification and digitalization effects on sectoral energy demand and consumption: a prospective study towards 2050, Li & Lepour 2023 {cite}`li2023electrification`
:icon: file-badge

**Abstract**

Energy transition is blurring the boundaries between the demand and supply sides with growing participation of prosumer resources. The intensifying pace of electrification and digitalization during the past decade tends to continue, leading to potential techno-economic-social challenges in energy strategy. However, it remains difficult to quantify their impacts on a national-level energy system, due to the trade-offs between increasing energy applications and decreasing energy consumption thanks to efficiency improvement. Using Switzerland as a case study, this work unveils the combined effects of (a) macro-economic drivers, (b) climate temperature rise, (c) system optimization, and (d) digitalization, on the end-use demand and final energy consumption in four major energy sectors, considering: industry, residence, mobility, and services. A systematic bottom-up and top-down approach was adopted, taking into account historical data by sector. The results show that: (1) the overall electricity consumption tends to increase by 20%–32%, while fuel consumption drops by 38%–95%, leading to (2) a total energy consumption reduction by 16%–59%, including the contribution from digitalization 10%–30%. (3) ICT (Information and Communication Technologies) is likely to become increasingly energy intensive, accounting for 25%–35% of electricity consumption, but can play an energy-supplying role through (4) data center heat recovery, promising to cut 15% national heating demand. Finally, the study highlights the importance of an early planning on investment decision and system operation to accommodate the development of electrification and digitalization, in order to meet the carbon neutrality target by 2050.
:::

:::{dropdown} {bdg-primary}`Journal` Decomposition strategy for districts as renewable energy hubs, Middelhauve 2022 {cite}`middelhauveDecompositionStrategyDistricts2022`
:icon: file-badge

**Abstract**

In light of the energy transition, it becomes a widespread solution to decentralize and to decarbonize energy systems. However, limited transformer capacities are a hurdle for large-scale integration of solar energy in the electricity grid. The aim of this paper is to define a novel concept of renewable energy hubs and to optimize its design strategy at the district scale in an appropriate computational time. To overcome runtime issues, the Dantzig–Wolfe decomposition method is applied to a mixed-integer linear programming framework of the renewable energy hub. Distributed energy units as well as centralized district units are considered. In addition, a method to perform multi-objective optimization as well as respecting district grid constraints in the decomposition algorithm is presented. The decomposed formulation leads to a convergence below 20 min for 31 buildings and a mip gap lower than 0.2%. The centralized design enhances the photovoltaic penetration in the energy mix and reduces the global warming potential and necessary curtailment in order to respect transformer capacity constraints.
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:::{dropdown} {bdg-primary}`Conference` Decentralized ICT integration in residential buildings, Lepour 2022 {cite}`lepourDecentralizedICTIntegration2022`
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*International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS) - July 3-7, 2022, Copenhagen, Denmark*

**Abstract**

To answer the growing demand for data computing, data storage and data transmission, the current trend is to construct centralized hyperscale data centers, whose power usage effectiveness (PUE) has substantially improved in recent years. Still, the operation of hyperscale data centers has economic and environmental impacts on society, especially if their residual heat is not reused. This study aims to present the economic and environmental rationales of decentralized computing capacities integrated into the building stock. The proposed solution simultaneously tackles the mitigation of greenhouse gas emissions from the residential sector and the ever-increasing global data demand, by exploiting the synergy between domestic thermal needs and digital services, while integrating PV production. The originality of this work resides in its holistic approach and multi-services (data, heat and electricity) dimension. A Mixed Integer Linear Programming (MILP) energy modelling optimization framework is developed to assess the economic and environmental performance of centralized hyperscale infrastructures versus decentralized building-integrated computing units with heat recovery. Results for the decentralized solution underline the reduction of environmental impact (-16.3%) and global cost (-27.7%) for the benefits of the whole society. As part of an integrated system, these decentralized computing units foster PV penetration, avoid the oversizing of a heat pump, and achieve high self-consumption (96%), while preventing the installation of a battery through coordination between thermal storage, data services and solar availability. This efficient solution offering an unmatched energy reuse effectiveness (ERE) shows the whole potential of the digitalization of energy systems, is a key contribution to building energy systems design, and reveals a promising approach to mitigate the increasing energy consumption of the ICT sector.
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:::{dropdown} {bdg-primary}`Conference` Potential of electric mobility as service to the grid in renewable energy hubs, Terrier 2022
:icon: globe

*International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS) - July 3-7, 2022, Copenhagen, Denmark*

**Abstract**

The electrification of private mobility is becoming a popular solution to reduce the reliance on fossil fuels. However, uncontrollable charging of a large electric vehicle fleet challenges the distribution grid due to transmission bottlenecks, voltage limit violation or excessive wearing. In contrast, the additional storage capacities represent a potential flexibility service for grid operators. Therefore, the optimal integration of electric vehicles in urban multi-energy systems is key to minimize the power grid reliance and to maximize the self-consumption of renewable energy resources. The aim of this paper is to integrate electric mobility in the concept of a renewable energy hub formulated at the district scale. The model is a mixed-integer linear programming problem, and the Dantzig-Wolfe decomposition is applied to reduce the computational time. The electric vehicles are considered as controllable reserves offering services to grid operators. An electric mobility integration of 20% is considered. The results demonstrated the economic feasibility of electric mobility integration where services to the grid allowed for a 70% reduction in charging costs and a 50% reduction in global warming potential. The grid services allowed for an increase in self-consumption (70% with respect to 55%) and the charging of the vehicle was managed by up to 82% of renewable electricity. The optimal battery management of the vehicles demonstrated peak load reductions and promoted a grid-aware design of the renewable energy hub.
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:::{dropdown} {bdg-primary}`Journal` Potential of photovoltaic panels on building envelopes for decentralized district energy systems, Middelhauve 2021 {cite}`middelhauve2021potential`
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**Abstract**

The expected increase of the penetration of distributed renewable energy technologies into the electricity grid is expected to lead to major challenges. As a main stakeholder, authorities often lack the appropriate tools to frame and encourage the transition and monitor the impact of energy transition policies. This paper aims at combining relatively detailed modeling of the PV generation potential on the building's envelope while retaining the energy system optimization approach. The problem is addressed as a multiobjective, mixed-integer linear programming problem. Compared to the existing literature in the field, the proposed approach combines advanced modeling of the energy generation potential from PV panels with detailed representation of the district energy systems, thus allowing an accurate representation of the interaction between the energy generation from PV and the rest of the system. The proposed approach was applied to a typical residential district in Switzerland. The results of the application of the proposed method show that the district can achieve carbon neutrality based on PV energy alone, but this requires covering all the available district's rooftops and part of the district's facades. Whereas facades are generally disregarded due to their lower generation potential, the results also allow concluding that facade PV can be economically convenient for a wide range of electricity prices, including those currently used by the Swiss grid operators. Achieving self-sufficiency at district scale is challenging: it can be achieved by covering approximately 42–100% of the available surface when the round-trip efficiency decreases from 100 to 50%. The results underline the importance of storage for achieving self-sufficiency: even with 100%, round-trip efficiency for the storage, very large capacities are required. However, energy demand reduction through renovation would allow reaching self-sufficiency with half of the PV and storage capacity required.
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:::{dropdown} {bdg-primary}`Journal` Grid-aware layout of photovoltaic panels in sustainable building energy systems, Middelhauve 2021 {cite}`middelhauve2021gridaware`
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**Abstract**

In the context of increasing concern for anthropogenic CO<sub>2</sub> emissions, the residential building sector still represents a major contributor to energy demand. The integration of renewable energy sources, and particularly of photovoltaic (PV) panels, is becoming an increasingly widespread solution for reducing the carbon footprint of building energy systems (BES). However, the volatility of the energy generation and its mismatch with the typical demand patterns are cause for concern, particularly from the viewpoint of the management of the power grid. This paper aims to show the influence of the orientation of photovoltaic panels in designing new BES and to provide support to the decision making process of optimal PV placing. The subject is addressed with a mixed integer linear optimization problem, with costs as objectives and the installation, tilt, and azimuth of PV panels as the main decision variables. Compared with existing BES optimization approaches reported in literature, the contribution of PV panels is modeled in more detail, including a more accurate solar irradiation model and the shading effect among panels. Compared with existing studies in PV modeling, the interaction between the PV panels and the remaining units of the BES, including the effects of optimal, scheduling is considered. The study is based on data from a residential district with 40 buildings in western Switzerland. The results confirm the relevant influence of PV panels' azimuth and tilt on the performance of BES. Whereas south-orientation remains the most preferred choice, west-orientationed panels better match the demand when compared with east-orientationed panels. Apart from the benefits for individual buildings, an appropriate choice of orientation was shown to benefit the grid: rotating the panels 20° westwards can, together with an appropriate scheduling of the BES, reduce the peak power of the exchange with the power grid by 50% while increasing total cost by only 8.3%. Including the more detailed modeling of the PV energy generation demonstrated that assuming horizontal surfaces can lead to inaccuracies of up to 20% when calculating operating expenses and electricity generated, particularly for high levels of PV penetration.
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:::{dropdown} {bdg-primary}`Journal` Contribution of model predictive control in the integration of renewable energy sources within the built environment, Stadler 2018 {cite}`stadler2018contributionMPC`
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**Abstract**

Integrating intermittent renewable energy sources has renders the power network operator task of balancing electricity generation and consumption increasingly challenging. Aside from heavily investing in additional storage capacities, an interesting solution might be the use predictive control methods to shift controllable loads toward production periods. Therefore, this article introduces a systematic approach to provide a preliminary evaluation of the thermoeconomic impact of model predictive control (MPC) when being applied to modern and complex building energy systems (BES). The proposed method applies an ϵ-constraint multi-objective optimization to generate a large panel of different BES configurations and their respective operating strategies. The problem formulation relies on a holistic BES framework to satisfy the different building service requirements using a mixed-integer linear programming technique. To illustrate the contribution of MPC, different applications on the single- and multi-dwelling level are presented and analyzed. The results suggest that MPC can facilitate the integration of renewable energy sources within the built environment by adjusting the heating and cooling demand to the fluctuating renewable generation, increasing the share of self-consumption by up to 27% while decreasing the operating expenses by up to 3% on the single-building level. Finally, a preliminary assessment of the national-wide potential is performed by means of an extended implementation on the Swiss building stock.
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:::{dropdown} {bdg-primary}`Journal` Model-based optimization of distributed and renewable energy systems in buildings, Stadler 2016 {cite}`stadler2016modelbased`
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**Abstract**

In order to fully exploit the potential of renewable energy resources (RERs) for building applications, optimal design and control of the different energy systems is a compelling challenge to address. This paper presents a two-step multi-objective optimization approach to size both thermal and electrical energy systems in regard of thermo-economic performance indicators to suit consumer and grid operator interests. Several utilities such as storage, conversion systems, and RERs are hence modeled and formulated through mixed-integer linear programming. Simultaneously, the algorithm defines the optimal operation strategy, based on a model predictive control structure, for each deterministic unit embedded within the energy management system of the building to meet the different comfort and service requirements. The developed design framework is successfully applied on several energy systems configuration of typical Swiss building types. Different component sizes are analyzed, regarding the present investment cost and the self-consumption share. In addition, this paper presents a novel optimal design criteria based on the maximum cost benefits in the view of both the consumer and the distribution network operator.
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### Contributions and projects

An important number of research projects have been carried out using REHO.
While the following reports did not experience a peer-review process, they still offer interesting applications of REHO.

:::{dropdown} {bdg-primary-line}`Research` The energy cost of living, Loustau 2024
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**Abstract**

The households have consented to pay a certain amount of money to heat and light themselves. How much money does it represent and what could be done with that money?

Based on the energy expenses reported in energy statistics for the last 20 years, it is possible to determine the cost of energy in constant Swiss francs of the energy used in buildings and therefore to calculate how much Swiss citizens have agreed to pay to be heated in the last years. Based on the building inventory and considering the reported heating system in the building, one can calculate for each building what would be the cost of heating the buildings based on the cost of the past. This allows indeed to calculate the cost of the business as usual case where the energy system and the building's envelop are not retrofitted. This value is then used as a reference to test different business models for the renovation of the buildings.
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:::{dropdown} {bdg-primary-line}`Research` Techno-economic study of local energy community in the Canton of Geneva, Suermondt 2023 {cite}`suermondtTechnoeconomicStudyLocal2023`
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**Abstract**

In a context of climate change, energy saving becomes a priority. The residential sector accounts for 20% of the final global energy use, which underlines the imperative to decarbonize city energy systems. This trend is anticipated to be driven by increased electrification, the development of distributed renewable energy and the emergence of prosumers who both consume and supply electricity to the grid. Maximizing self-consumption and self-sufficiency at the building level can help manage the issue of renewable energy penetration in the energy mix but may not fully address it. Implementing local energy communities (CEL), offers perspectives by sharing energy among nearby stakeholders inside a neighborhood. However, CEL implementation would require changes in business models of power utilities and distribution system operators (DSO) as they are expected to sell less energy. Besides, it also implies having a proper delineation of a neighborhood which is for the moment unclear. This work aims to answer those two problems at the level of the canton of Geneva.

First, the GIREC subdivision of the canton was found to be the most appropriate after comparing different zonings. Clustering with Gaussian mixture model (GMM) allowed to found 4 neighborhood archetypes that give energetic characteristics for each GIREC neighborhood. Second, the financial analysis of a CEL implementation in a residential neighborhood (Les Vergers) allowed to estimate the changes in business models that would be required for the different stakeholders of the grouping. The DSO is the only stakeholder who faces revenue losses: it looses at least 10% compared to a simple RCP (Regroupement de Consommation Propre) scenario but the local distribution charge allows to mitigate its losses. The DSO captures at least 33 kCHF in the case study compared to a RCP microgrid scenario. Increasing the power component of the DSO pricing with a cheaper electricity price for PV panel production than in a RCP could transfer revenue from PV panels owners to the DSO while ensuring fairness among stakeholders.
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:::{dropdown} {bdg-primary-line}`Research` Grid integration of PV systems: a comprehensive study of the effects of heating and mobility electrification on the low voltage grid of Geneva, Chrysanthou 2023
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**Abstract**

Many energy policies set a goal of decreasing the carbon emissions of the energy sector by up to 100%, including the electricity grid. This is a long term and gradual process. Energy systems in neighbourhoods will likely be the starting point for greenhouse gas emissions mitigation since they account for 70% of global carbon emissions. This work, in collaboration with the Industrial Services of Geneva (SIG) and the IPESE laboratory at EPFL, examines the influence of grid-connected PV systems, heating electrification, and mobility electrification on the low voltage grid. The study utilizes the Renewable Energy Hub Optimizer (REHO) to simulate neighbourhood behaviors under diverse horizons and technologies penetrations. A case study is performed in three neighbourhoods in Geneva with different grid structures namely Rural, Villa and Residential. The Rural having lower density and high PV potential, Villa more density but lower PV potential and Residential with high density and low PV potential. The results are then extrapolated, with the help of clustering, to offer a global view of the future needs and PV production of the canton of Geneva. A financial analysis is then conducted to propose tailored solutions to the local Distribution System Operator (DSO). Results suggest that District Heating Networks (DHN) are particularly important in Residential neighbourhoods in order to optimise their CO2 emissions and energy demand. Furthermore this study shows that without a DHN, the Residential neighbourhood can support only 30% of electric mobility with the current grid structure. It also suggests that with the current grid structure the Rural and Villa neighbourhoods will have to curtail part of the PV production. Finally the study argues that for the Rural cluster network expansion is the most suitable solution in the long-term, and for the Villa cluster a combination of transformer replacement and paid flexibility is best. Nevertheless, the study shows that the expansion of the grid without storage does not offer significant advantages in exploiting the full potential of PV production.
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:::{dropdown} {bdg-primary-line}`Development` Demand aggregation in a district energy system perspective, Lacorte 2023 {cite}`lacorteDemandAggregationDistrict`
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**Abstract**

The discrepancy between energy production and consumption poses a challenge in optimizing energy systems. This mismatch often results in imbalances, where energy surplus or deficit occurs at different times. The objective is therefore to find a solution to compensate for this time difference. To address this issue, the concept of pooling of energy balance through energy communities has emerged as a solution. By sharing energy demand and equipment within a district, energy communities enable the compensation between excess and deficit. One crucial aspect of pooling energy balance is the consideration of the stochastic effect. The consumption curve, affected by the variability in individual behaviors, can be smoothed through the mutualisation of buildings within an energy community. This smoothing effect reduces peak consumption and enhances the overall stability of the energy system. This article contributes to highlight the benefits of pooling energy demand and equipment sharing at the district level. By analyzing the benefits of energy communities and incorporating the stochastic effect, the article exposes the potential for optimising energy systems within districts. The findings contribute to a better understanding of how pooling of energy balance can lead to improved energy efficiency, resource management and sustainability within urban communities.
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:::{dropdown} {bdg-primary-line}`Development` Integration of cooling service in buildings energetics, Aviolat 2022 {cite}`aviolat2022cooling`
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Integration of the cooling technologies in the model.
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:::{dropdown} {bdg-primary-line}`Research` Analyse énergétique du quartier des Vergers à Genève, Lepour 2022
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Ce rapport propose une analyse énergétique du Quartier des Vergers, situé dans le canton de Genève, à l'aide des outils QBuildings et Renewable Energy Hub Optimizer (REHO) développés au sein du laboratoire Industrial Process and Energy Systems Engineering (IPESE) de l'EPFL.

https://ipese-web.epfl.ch/lepour/vergers.html
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:::{dropdown} {bdg-primary-line}`Research` Analyse énergétique du quartier du Jardin des Nations à Genève, Lepour 2022
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Ce rapport propose une analyse énergétique du Jardin des Nations, situé dans le canton de Genève, à l'aide des outils QBuildings et Renewable Energy Hub Optimizer (REHO) développés au sein du laboratoire Industrial Process and Energy Systems Engineering (IPESE) de l'EPFL.

https://ipese-web.epfl.ch/lepour/nations.html
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:::{dropdown} {bdg-primary-line}`Research` Contribution of storage technologies to renewable energy hubs, Mathieu 2021 {cite}`mathieuContributionStorageTechnologies2022`
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**Abstract**

A holistic approach, considering all the energy needs of a territory, should be adopted in the challenge of the energy transition. Synergies between the different end-use demand sectors must be developed, in order to optimize the efficient use of resources. The multi-energy system of the future will be integrated and coordinated, with renewable energy sources and decentralized capacities. Indeed, in a context of increasing urbanization worldwide, decentralized renewable capacities appear to be the key driver to decarbonize urban environments and foster the emergence of renewable energy hubs. Mutualized infrastructures need to be deployed at every stage of these hubs: from energy harvesting, transport, and storage; to mobility services and goods production. The most suited scope to study the deployment and promotion of these local capacities and shared infrastructures appears to be the district perspective. The financial and environmental benefits of a district integrated approach for the mutualization of capacities have been proved, but their implementation mechanisms remain understudied. The aim of this study is to characterize the contribution of storage technologies to ensure the energy balance of a territory, assess the associated investments to be made, and discuss the techno-economic and environmental performance of the whole system. Firstly, a district is defined as a renewable energy hub, by identifying the energy needs of the residents and the potential of endogenous resources. Then, a Mixed Integer Linear Programming (MILP) model is developed to offer a multi-objective optimization of energy resources at district-level. Finally, a characterization of the storage technologies available under the horizon 2050 is conducted and a set of technological solutions is created to serve as input to the optimization model. Although their robustness has not been assessed, the obtained results show several interesting impacts. First, storage implantation allows to foster Photovoltaic (PV) deployment until full penetration. Sides effects to this increased penetration are a growth of the exported electricity together with a reduction of the imports. While the the latter is beneficial, the export increase might put the electric grid at risk. Second, synergies between electric and heat storage technologies where demonstrated through an increased use of heat technologies. Lastly, long term storage was not demonstrated and additional work should be undertaken to validate the overall model.
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:::{dropdown} {bdg-primary-line}`Research` Optimal design and operation of district energy systems using Dantzig Wolfe decomposition, Terrier 2021
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Development of a decomposition algorithm for district-scale optimization.
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## References

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