Periodic Reporting for period 1 - NextENERGEIA (Simulating the effects of low-carbon investments in electricity markets)
Reporting period: 2024-03-01 to 2025-03-31
The energy transition requires massive investments in low-carbon technologies—renewables, storage, green hydrogen, and flexible demand assets like data centers. However, whether these investments materialize hinges on the incentives faced by firms and households, which in turn depend on how electricity markets perform under evolving conditions. Today, regulators, investors, and policymakers lack robust tools to anticipate how market outcomes—such as prices, emissions, and investment profitability—will evolve under different scenarios. This information gap risks slowing the deployment of critical assets and misallocating public support.
NextENERGEIA addresses this need by developing a new software tool to simulate electricity market performance under various investment pathways and policy scenarios. Built on state-of-the-art game-theoretic models developed in the ERC project ELECTRIC CHALLENGES, the tool captures both competitive and strategic behavior of firms, models electricity markets at hourly resolution, and allows to assess investment decisions—features that are largely missing from existing tools.
In particular, NextENERGEIA is an accessible, modular, Python-based simulation engine that helps policymakers, firms, and researchers assess the private and social returns to low-carbon investments in electricity markets. The tool allows users to evaluate how different investment types (e.g. solar, storage, hydrogen) affect prices, emissions, and incentives, under current or hypothetical regulatory regimes.
The expected impact is threefold:
1. Policy relevance – Regulators and governments will gain a transparent, empirically grounded instrument to test reforms, design support schemes, and anticipate the economic effects of green investment policies.
2. Private decision-making – Investors and firms will be able to benchmark projects and forecast profitability under strategic market interactions.
3. Research and outreach – The tool will bridge the gap between academic modeling and applied policy work, offering open-access simulations and outputs adaptable across EU member states.
NextENERGEIA addresses this need by developing a new software tool to simulate electricity market performance under various investment pathways and policy scenarios. Built on state-of-the-art game-theoretic models developed in the ERC project ELECTRIC CHALLENGES, the tool captures both competitive and strategic behavior of firms, models electricity markets at hourly resolution, and allows to assess investment decisions—features that are largely missing from existing tools.
In particular, NextENERGEIA is an accessible, modular, Python-based simulation engine that helps policymakers, firms, and researchers assess the private and social returns to low-carbon investments in electricity markets. The tool allows users to evaluate how different investment types (e.g. solar, storage, hydrogen) affect prices, emissions, and incentives, under current or hypothetical regulatory regimes.
The expected impact is threefold:
1. Policy relevance – Regulators and governments will gain a transparent, empirically grounded instrument to test reforms, design support schemes, and anticipate the economic effects of green investment policies.
2. Private decision-making – Investors and firms will be able to benchmark projects and forecast profitability under strategic market interactions.
3. Research and outreach – The tool will bridge the gap between academic modeling and applied policy work, offering open-access simulations and outputs adaptable across EU member states.
The project builds on foundational research developed in the ERC Consolidator Grant ELECTRIC CHALLENGES, transforming theoretical models into a flexible, user-facing simulation environment.
Key activities and achievements include:
1. Model architecture design and implementation
The core simulation engine was built in Python using a modular design that supports different market configurations and agent types (price-taking or strategic generators). The model captures hourly electricity dispatch over a full year and allows to endogenize investment decisions for different technologies (solar, wind, storage, hydrogen, data centers.).
2. Model refinement
We improved the tractability and convergence of the equilibrium algorithm, ensuring the model runs efficiently.
3. Scenario simulation and sensitivity analysis
As part of the testing, we used the tool to simulate counterfactual investment pathways under different assumptions—such as the early closure of nuclear plants, varying CO2 prices, and public support schemes for storage or hydrogen. These simulations show how prices, emissions, capacity mix, and producer profits vary with technology, policy, and market structure.
Outcomes of the Action
The NextENERGEIA prototype is operational and ready for pilot use by researchers and analysts. It provides:
• A flexible platform for evaluating electricity market outcomes under investment and policy scenarios
• A robust equilibrium engine capable of simulating firm behavior
The tool has already been used in ongoing academic work and internal policy briefings and lays the groundwork for future collaborations with regulators and public institutions. Technically, the project demonstrates that academic electricity market models can be translated into applied tools, offering both scientific depth and policy usability.
Key activities and achievements include:
1. Model architecture design and implementation
The core simulation engine was built in Python using a modular design that supports different market configurations and agent types (price-taking or strategic generators). The model captures hourly electricity dispatch over a full year and allows to endogenize investment decisions for different technologies (solar, wind, storage, hydrogen, data centers.).
2. Model refinement
We improved the tractability and convergence of the equilibrium algorithm, ensuring the model runs efficiently.
3. Scenario simulation and sensitivity analysis
As part of the testing, we used the tool to simulate counterfactual investment pathways under different assumptions—such as the early closure of nuclear plants, varying CO2 prices, and public support schemes for storage or hydrogen. These simulations show how prices, emissions, capacity mix, and producer profits vary with technology, policy, and market structure.
Outcomes of the Action
The NextENERGEIA prototype is operational and ready for pilot use by researchers and analysts. It provides:
• A flexible platform for evaluating electricity market outcomes under investment and policy scenarios
• A robust equilibrium engine capable of simulating firm behavior
The tool has already been used in ongoing academic work and internal policy briefings and lays the groundwork for future collaborations with regulators and public institutions. Technically, the project demonstrates that academic electricity market models can be translated into applied tools, offering both scientific depth and policy usability.
Results Overview
The project has delivered a working prototype of NextENERGEIA—a modular, data-driven simulation tool that quantifies the effects of low-carbon investment on prices, emissions, and welfare outcomes. The tool integrates investment and dispatch decisions in a general framework, based on strategic or competitive behavior by firms. It is fully implemented in Python, adaptable to analyze any liberalized electricity market around the world.
Potential Impacts
• Better energy policy design: Policymakers can use the tool to anticipate the market effects of regulatory reforms, CO2 pricing, technology mandates, or public support schemes, among others.
• More informed investment decisions: Investors and utilities gain insight into long-term profitability under different market and policy scenarios, supporting capital allocation toward technologies like storage, hydrogen, or renewables.
• Bridging academia and policy: The tool operationalizes state-of-the-art economic modeling in a usable format for real-world stakeholders, helping reduce the gap between academic research and applied decision-making.
• Scalability to other EU markets: Although initially tested on Spain, the framework is general and can be calibrated to any EU member state, facilitating harmonized planning, scenario testing, and cross-border analysis.
Key Needs for Further Uptake and Success
1. Further research and model development: Continued refinement is needed to better endogenize cross-border trading behavior.
2. Demonstration and stakeholder testing: Pilot use by public agencies and regulatory bodies will be key to validating usability and ensuring the tool addresses practical decision-making needs.
3. Access to market and finance datasets: Wider deployment requires access to detailed, country-level electricity market data—including generator characteristics, pricing data, and regulatory parameters.
4. Commercialisation and IPR strategy: While the tool is at the prototype stage, commercial pathways could support sustainability. An IPR framework will help clarify ownership and licensing terms.
5. Institutional partnerships: Long-term impact depends on partnerships with energy ministries, regulators, system operators, and international bodies like ACER or ENTSO-E at the EU level of the Competition and Regulatory Commission at the national level.
Summary of Results
• A validated prototype of the NextENERGEIA simulation tool
• A set of policy-relevant case studies for the Spanish market
• A scalable modeling architecture for broader EU use
• Initial engagement for testing and refinement
NextENERGEIA has the potential to become a key reference tool for analyzing electricity markets—helping to align public policy, private investment, and decarbonization goals.
The project has delivered a working prototype of NextENERGEIA—a modular, data-driven simulation tool that quantifies the effects of low-carbon investment on prices, emissions, and welfare outcomes. The tool integrates investment and dispatch decisions in a general framework, based on strategic or competitive behavior by firms. It is fully implemented in Python, adaptable to analyze any liberalized electricity market around the world.
Potential Impacts
• Better energy policy design: Policymakers can use the tool to anticipate the market effects of regulatory reforms, CO2 pricing, technology mandates, or public support schemes, among others.
• More informed investment decisions: Investors and utilities gain insight into long-term profitability under different market and policy scenarios, supporting capital allocation toward technologies like storage, hydrogen, or renewables.
• Bridging academia and policy: The tool operationalizes state-of-the-art economic modeling in a usable format for real-world stakeholders, helping reduce the gap between academic research and applied decision-making.
• Scalability to other EU markets: Although initially tested on Spain, the framework is general and can be calibrated to any EU member state, facilitating harmonized planning, scenario testing, and cross-border analysis.
Key Needs for Further Uptake and Success
1. Further research and model development: Continued refinement is needed to better endogenize cross-border trading behavior.
2. Demonstration and stakeholder testing: Pilot use by public agencies and regulatory bodies will be key to validating usability and ensuring the tool addresses practical decision-making needs.
3. Access to market and finance datasets: Wider deployment requires access to detailed, country-level electricity market data—including generator characteristics, pricing data, and regulatory parameters.
4. Commercialisation and IPR strategy: While the tool is at the prototype stage, commercial pathways could support sustainability. An IPR framework will help clarify ownership and licensing terms.
5. Institutional partnerships: Long-term impact depends on partnerships with energy ministries, regulators, system operators, and international bodies like ACER or ENTSO-E at the EU level of the Competition and Regulatory Commission at the national level.
Summary of Results
• A validated prototype of the NextENERGEIA simulation tool
• A set of policy-relevant case studies for the Spanish market
• A scalable modeling architecture for broader EU use
• Initial engagement for testing and refinement
NextENERGEIA has the potential to become a key reference tool for analyzing electricity markets—helping to align public policy, private investment, and decarbonization goals.