Pub Date : 2026-03-01Epub Date: 2026-02-10DOI: 10.1016/j.eneco.2026.109200
Xuhao Zhan , Bowei Guo
Decarbonizing the transportation sector is essential for meeting global climate targets. However, transportation electrification imposes substantial costs on power systems. This study develops a novel data-driven approach that leverages comprehensive grid measurement data to quantify these costs, referred to here as social costs. The results indicate that advancements in power transfer technologies, particularly vehicle-to-grid (V2G) integration, can substantially reduce social costs and, in some cases, generate net social benefits. When the proposed method is applied to two regions in China with contrasting power system characteristics, V2G leads to significant reductions in social costs in both low (Guangdong) and high (Gansu) renewable penetration regions. The reduction is greater in Gansu, primarily driven by a stronger decline in capacity investment costs, reflecting the greater reliance of high-renewable power systems on dispatchable capacity. Based on the estimated social costs, we propose a pricing mechanism to enable economically efficient V2G integration, demonstrating the first-best market-based mechanism and the second-best direct-pricing mechanism.
{"title":"Electric vehicles to the grid: Costs, benefits, and pricing mechanisms","authors":"Xuhao Zhan , Bowei Guo","doi":"10.1016/j.eneco.2026.109200","DOIUrl":"10.1016/j.eneco.2026.109200","url":null,"abstract":"<div><div>Decarbonizing the transportation sector is essential for meeting global climate targets. However, transportation electrification imposes substantial costs on power systems. This study develops a novel data-driven approach that leverages comprehensive grid measurement data to quantify these costs, referred to here as <em>social costs</em>. The results indicate that advancements in power transfer technologies, particularly vehicle-to-grid (V2G) integration, can substantially reduce social costs and, in some cases, generate net social benefits. When the proposed method is applied to two regions in China with contrasting power system characteristics, V2G leads to significant reductions in social costs in both low (Guangdong) and high (Gansu) renewable penetration regions. The reduction is greater in Gansu, primarily driven by a stronger decline in capacity investment costs, reflecting the greater reliance of high-renewable power systems on dispatchable capacity. Based on the estimated social costs, we propose a pricing mechanism to enable economically efficient V2G integration, demonstrating the first-best market-based mechanism and the second-best direct-pricing mechanism.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109200"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146152671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-01DOI: 10.1016/j.eneco.2026.109168
Qiang Tu , Limei Zuo , Jianlei Mo , Yaming Ma , Ye Yao , Qi Su
The 17 Sustainable Development Goals (SDGs) proposed in the 2030 Agenda for Sustainable Development includes ensuring access to sustainable modern energy, as well as reducing inequality within countries. These goals may interact with each other, but research examining the impact of renewable energy deployment on economic inequality remains limited. To fill this gap, we estimate a city-level Dagum Gini coefficient from county-level nighttime lights to measure regional economic inequality, providing a production-side proxy with fine spatial resolution. And the difference-in-difference (DID) model is utilized in this study to identify the impact of renewable energy deployment on regional economic inequality, using a unique full sample dataset of China's renewable energy projects from 2001 to 2020. The empirical results indicate that the renewable energy deployment reduces regional economic inequality. Specifically, for every 1 GW of biomass and solar PV deployed in a city, the Gini coefficient is reduced by approximately 0.038–0.064 and 0.018–0.020, respectively, while wind energy deployment seems to have minimal impact on regional economic inequality. This study further confirms that the promotion of rural employment and the upgrading of the industrial structure are key mechanisms through which renewable energy deployment contributes to reducing regional economic inequality. Furthermore, increased investment in education and improved transport infrastructure would enhance the effect of renewable energy deployment on reducing regional economic inequality. Consequently, this research offers valuable insights for the strategic deployment of renewable energy not only in China and other developing countries but also for policy makers endeavoring to create policy synergies aligned with the SDGs.
{"title":"Large scale renewable energy deployment reduces regional economic inequality:Evidence from China","authors":"Qiang Tu , Limei Zuo , Jianlei Mo , Yaming Ma , Ye Yao , Qi Su","doi":"10.1016/j.eneco.2026.109168","DOIUrl":"10.1016/j.eneco.2026.109168","url":null,"abstract":"<div><div>The 17 Sustainable Development Goals (SDGs) proposed in the 2030 Agenda for Sustainable Development includes ensuring access to sustainable modern energy, as well as reducing inequality within countries. These goals may interact with each other, but research examining the impact of renewable energy deployment on economic inequality remains limited. To fill this gap, we estimate a city-level Dagum Gini coefficient from county-level nighttime lights to measure regional economic inequality, providing a production-side proxy with fine spatial resolution. And the difference-in-difference (DID) model is utilized in this study to identify the impact of renewable energy deployment on regional economic inequality, using a unique full sample dataset of China's renewable energy projects from 2001 to 2020. The empirical results indicate that the renewable energy deployment reduces regional economic inequality. Specifically, for every 1 GW of biomass and solar PV deployed in a city, the Gini coefficient is reduced by approximately 0.038–0.064 and 0.018–0.020, respectively, while wind energy deployment seems to have minimal impact on regional economic inequality. This study further confirms that the promotion of rural employment and the upgrading of the industrial structure are key mechanisms through which renewable energy deployment contributes to reducing regional economic inequality. Furthermore, increased investment in education and improved transport infrastructure would enhance the effect of renewable energy deployment on reducing regional economic inequality. Consequently, this research offers valuable insights for the strategic deployment of renewable energy not only in China and other developing countries but also for policy makers endeavoring to create policy synergies aligned with the SDGs.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109168"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-25DOI: 10.1016/j.eneco.2026.109214
Anthony Garratt , Ivan Petrella , Yunyi Zhang
This paper investigates the information content of oil market forecasts produced by the U.S. Energy Information Administration (EIA). We evaluate the maximum informative forecast horizons for EIA projections of world and U.S. oil demand, supply, inventories, and prices. Our results show that U.S. forecasts are systematically more informative than their global counterparts, with content horizons extending up to six quarters for most U.S. variables. The information content embedded in EIA forecasts reflects both the agency’s ability to track evolving market conditions and, particularly at short horizons, the incorporation of information that goes beyond simple trend extrapolation.
{"title":"The predictive content of U.S. Energy Information Administration oil market forecasts","authors":"Anthony Garratt , Ivan Petrella , Yunyi Zhang","doi":"10.1016/j.eneco.2026.109214","DOIUrl":"10.1016/j.eneco.2026.109214","url":null,"abstract":"<div><div>This paper investigates the information content of oil market forecasts produced by the U.S. Energy Information Administration (EIA). We evaluate the maximum informative forecast horizons for EIA projections of world and U.S. oil demand, supply, inventories, and prices. Our results show that U.S. forecasts are systematically more informative than their global counterparts, with content horizons extending up to six quarters for most U.S. variables. The information content embedded in EIA forecasts reflects both the agency’s ability to track evolving market conditions and, particularly at short horizons, the incorporation of information that goes beyond simple trend extrapolation.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"156 ","pages":"Article 109214"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147351234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-03DOI: 10.1016/j.eneco.2026.109159
Alexandra Serebriakova (Sasha) , Friedemann Polzin , Mark Sanders
Policymakers have raised concerns that the required transition to renewable energy sources in the European Union could be stalled by a period of higher ECB policy rates meant to combat inflation. Prior research shows heterogeneous effects of policy rates on sectors with varying industrial characteristics, meaning that renewable technologies may be hit disproportionately by monetary contractions due to their investment requirements, life-cycle stage, and/or dependence on external finance. This paper uses fixed effects panel analysis of 28 European countries to look at the interactions between installed capacity of 10 utility-scale energy technologies, their characteristics, and monetary policy. Over the period of 2001–2024, fossil fuel, hydropower and nuclear technologies remained unaffected by monetary contractions, while a 25 basis point rise in policy rates was associated with a 3.2% decrease in total installed capacity for onshore wind, and a 5.3% decrease for solar PV. Significant interaction effects, using measures of investment intensity and external finance dependence for energy technologies, yield evidence in favour of the interest rate and balance sheet channels of monetary policy transmission. To address endogeneity concerns, we use a two-stage least squares (2SLS) approach in an LCOE specification for the interest rate channel in the energy sector, which confirms these findings. Our results suggest the existence of an unintended bias in contractionary monetary operations; central banks should consider flanking policies (such as preferred interest rates) to offset the disadvantage for renewables.
{"title":"Monetary policy and energy installation: Implications for the European green transition","authors":"Alexandra Serebriakova (Sasha) , Friedemann Polzin , Mark Sanders","doi":"10.1016/j.eneco.2026.109159","DOIUrl":"10.1016/j.eneco.2026.109159","url":null,"abstract":"<div><div>Policymakers have raised concerns that the required transition to renewable energy sources in the European Union could be stalled by a period of higher ECB policy rates meant to combat inflation. Prior research shows heterogeneous effects of policy rates on sectors with varying industrial characteristics, meaning that renewable technologies may be hit disproportionately by monetary contractions due to their investment requirements, life-cycle stage, and/or dependence on external finance. This paper uses fixed effects panel analysis of 28 European countries to look at the interactions between installed capacity of 10 utility-scale energy technologies, their characteristics, and monetary policy. Over the period of 2001–2024, fossil fuel, hydropower and nuclear technologies remained unaffected by monetary contractions, while a 25 basis point rise in policy rates was associated with a 3.2% decrease in total installed capacity for onshore wind, and a 5.3% decrease for solar PV. Significant interaction effects, using measures of investment intensity and external finance dependence for energy technologies, yield evidence in favour of the interest rate and balance sheet channels of monetary policy transmission. To address endogeneity concerns, we use a two-stage least squares (2SLS) approach in an LCOE specification for the interest rate channel in the energy sector, which confirms these findings. Our results suggest the existence of an unintended bias in contractionary monetary operations; central banks should consider flanking policies (such as preferred interest rates) to offset the disadvantage for renewables.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109159"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146111041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-06DOI: 10.1016/j.eneco.2026.109173
Vedanshi Nevatia
Sovereign green bonds have emerged as a prominent policy instrument to mobilize climate finance, yet evidence on their pricing implications, especially across development levels and relative to unlabeled sustainability bonds, remains limited. This study provides the first global, bond-level analysis of sovereign green and sustainability bond pricing in secondary markets across advanced and emerging economies. Using Bloomberg data on 168 sovereign sustainability bonds issued between 2017 and 2023 across 44 countries, the analysis employs coarsened exact matching to estimate the greenium for green-labeled as well as unlabeled bonds. The results reveal strong regional heterogeneity. In advanced economies, sovereign green bonds trade at a positive yield premium of 20–40 basis points. In contrast, EMDEs exhibit a significant sovereign greenium of approximately 10 basis points for green-labeled bonds, alongside a positive premium for unlabeled sustainability bonds. This suggests that green labeling is associated with lowered perceived risk and informational asymmetry. This is especially true for riskier countries, speculative-grade bonds, and during periods of financial volatility. Overall, the results highlight that while sovereign green bonds may act as effective risk-mitigating instruments for climate finance in emerging economies, institutional heterogeneity and market structures have a role to play in shaping sustainability bond issuances.
{"title":"Sovereign green bonds: Risk-mitigating sustainability instruments in emerging markets","authors":"Vedanshi Nevatia","doi":"10.1016/j.eneco.2026.109173","DOIUrl":"10.1016/j.eneco.2026.109173","url":null,"abstract":"<div><div>Sovereign green bonds have emerged as a prominent policy instrument to mobilize climate finance, yet evidence on their pricing implications, especially across development levels and relative to unlabeled sustainability bonds, remains limited. This study provides the first global, bond-level analysis of sovereign green and sustainability bond pricing in secondary markets across advanced and emerging economies. Using Bloomberg data on 168 sovereign sustainability bonds issued between 2017 and 2023 across 44 countries, the analysis employs coarsened exact matching to estimate the <em>greenium</em> for green-labeled as well as unlabeled bonds. The results reveal strong regional heterogeneity. In advanced economies, sovereign green bonds trade at a positive yield premium of 20–40 basis points. In contrast, EMDEs exhibit a significant sovereign <em>greenium</em> of approximately 10 basis points for green-labeled bonds, alongside a positive premium for unlabeled sustainability bonds. This suggests that green labeling is associated with lowered perceived risk and informational asymmetry. This is especially true for riskier countries, speculative-grade bonds, and during periods of financial volatility. Overall, the results highlight that while sovereign green bonds may act as effective risk-mitigating instruments for climate finance in emerging economies, institutional heterogeneity and market structures have a role to play in shaping sustainability bond issuances.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109173"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-17DOI: 10.1016/j.eneco.2026.109209
Anna Creti , Alpha Ly , Maria-Eugenia Sanin
Energy poverty is a multidimensional issue, as demonstrated by a comparison between two low-income countries, Bolivia (BOL) and Côte d’Ivoire (CIV), and a high-income European country, France (FRA). These three countries represent different stages of access and energy poverty. CIV lags behind BOL and FRA in electricity access but still contends with energy poverty. However, both BOL and CIV face significant energy affordability issues, leading to widespread energy poverty. Moreover, BOL and CIV have very low access to clean cooking, while BOL has achieved universal access to electricity, similar to FRA. This study examines the socio-economic determinants of access to energy infrastructure, energy services, and energy poverty. It finds that as the share of households with access to energy and services increases, the likelihood of an energy poverty trap also rises. The energy-poverty gap, which is the total cash transfer needed to address energy poverty, is higher in BOL and FRA compared to CIV due to higher average energy expenditures and a larger number of energy-poor households. Using clustering techniques, our study identifies the socio-demographic profiles of the most vulnerable households. Targeting these groups is shown to be more effective in bridging the energy poverty gap. Our findings highlight the importance of considering affordability in efforts to ensure universal energy access, to prevent further exclusion, and promote energy justice.
{"title":"Energy Poverty has a justice dimension: Comparing Bolivia, Côte d’Ivoire and France","authors":"Anna Creti , Alpha Ly , Maria-Eugenia Sanin","doi":"10.1016/j.eneco.2026.109209","DOIUrl":"10.1016/j.eneco.2026.109209","url":null,"abstract":"<div><div>Energy poverty is a multidimensional issue, as demonstrated by a comparison between two low-income countries, Bolivia (BOL) and Côte d’Ivoire (CIV), and a high-income European country, France (FRA). These three countries represent different stages of access and energy poverty. CIV lags behind BOL and FRA in electricity access but still contends with energy poverty. However, both BOL and CIV face significant energy affordability issues, leading to widespread energy poverty. Moreover, BOL and CIV have very low access to clean cooking, while BOL has achieved universal access to electricity, similar to FRA. This study examines the socio-economic determinants of access to energy infrastructure, energy services, and energy poverty. It finds that as the share of households with access to energy and services increases, the likelihood of an energy poverty trap also rises. The energy-poverty gap, which is the total cash transfer needed to address energy poverty, is higher in BOL and FRA compared to CIV due to higher average energy expenditures and a larger number of energy-poor households. Using clustering techniques, our study identifies the socio-demographic profiles of the most vulnerable households. Targeting these groups is shown to be more effective in bridging the energy poverty gap. Our findings highlight the importance of considering affordability in efforts to ensure universal energy access, to prevent further exclusion, and promote energy justice.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109209"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147278524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-06DOI: 10.1016/j.eneco.2026.109167
Clemens Stiewe , Alice Lixuan Xu , Anselm Eicke , Lion Hirth
{"title":"Corrigendum to “Cross-border cannibalization: Spillover effects of wind and solar energy on interconnected European electricity markets” [Energy Economics, 143, March 2025, 108251]","authors":"Clemens Stiewe , Alice Lixuan Xu , Anselm Eicke , Lion Hirth","doi":"10.1016/j.eneco.2026.109167","DOIUrl":"10.1016/j.eneco.2026.109167","url":null,"abstract":"","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109167"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-19DOI: 10.1016/j.eneco.2026.109203
Szabolcs Blazsek , Álvaro Escribano , Erzsébet Kristóf
We employ a novel score-driven climate clustering model to analyze global climate change from January 1940 to December 2024. This model dynamically reclassifies global geographic locations using climate variables from ERA5, which is the fifth-generation reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). The dataset includes monthly data from 930 uniformly distributed locations worldwide, covering eight variables: air temperature at 2 m, dew point temperature at 2 m, mean sea level pressure, eastward component of the 10-meter wind, northward component of the 10-meter wind, 10-meter wind gust, total precipitation, and downward short-wave solar radiation flux at the Earth’s surface. Our climate clustering model is a multivariate, score-driven, multi-regime-switching framework that analyzes the conditional mean and covariance matrix of these climate variables. It specifies a dynamic transition probability matrix for the different climate regimes, effectively representing climate clusters. We estimate the transition, filtered, and predictive probabilities for each climate regime. We focus on five distinct climate clusters. We present the evolution of the predictive probabilities for these clusters across various geographic locations experiencing observable climate change. Additionally, we explore alternative data and model specifications, guided by the feasibility of statistical estimation. Our findings include an annual analysis of 110 uniformly distributed locations worldwide for two variables: air and dew point temperatures at 2 m. The results indicate several geographic locations in both the Northern and Southern Hemispheres that transition to higher temperature clusters throughout the sample period.
{"title":"Score-driven global climate zones from 1940 to 2024: A new objective climate classification method","authors":"Szabolcs Blazsek , Álvaro Escribano , Erzsébet Kristóf","doi":"10.1016/j.eneco.2026.109203","DOIUrl":"10.1016/j.eneco.2026.109203","url":null,"abstract":"<div><div>We employ a novel score-driven climate clustering model to analyze global climate change from January 1940 to December 2024. This model dynamically reclassifies global geographic locations using climate variables from ERA5, which is the fifth-generation reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). The dataset includes monthly data from 930 uniformly distributed locations worldwide, covering eight variables: air temperature at 2 m, dew point temperature at 2 m, mean sea level pressure, eastward component of the 10-meter wind, northward component of the 10-meter wind, 10-meter wind gust, total precipitation, and downward short-wave solar radiation flux at the Earth’s surface. Our climate clustering model is a multivariate, score-driven, multi-regime-switching framework that analyzes the conditional mean and covariance matrix of these climate variables. It specifies a dynamic transition probability matrix for the different climate regimes, effectively representing climate clusters. We estimate the transition, filtered, and predictive probabilities for each climate regime. We focus on five distinct climate clusters. We present the evolution of the predictive probabilities for these clusters across various geographic locations experiencing observable climate change. Additionally, we explore alternative data and model specifications, guided by the feasibility of statistical estimation. Our findings include an annual analysis of 110 uniformly distributed locations worldwide for two variables: air and dew point temperatures at 2 m. The results indicate several geographic locations in both the Northern and Southern Hemispheres that transition to higher temperature clusters throughout the sample period.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"156 ","pages":"Article 109203"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-02-11DOI: 10.1016/j.eneco.2026.109195
Julien Ancel
This article investigates different types of actors controlling demand response (DR) operations under Cournot competition. Analytical results linking shiftable load level, market equilibrium, and welfare are obtained for DR operated either by an independent aggregator (price-taker or price-maker), by end-consumers’ suppliers, or within the portfolio of generators. An application to a 2035 French power system with detailed flexible appliances constraints is also proposed. Results show that supplier-integrated DR yields the greatest price reductions and lowest shiftable load withholding, while DR integrated with baseload producers has the weakest effects on prices and may worsen welfare losses compared to a perfectly competitive market. While DR deployment consistently improves welfare and lowers prices, the extent depends on the control structure. Independent aggregation and supplier integration deliver similar welfare gains but shift surplus toward consumers, whereas integration within generators results in up to a 6€/MWh higher producer surplus compared to the other structures. Policy implications highlight the importance of DR deployment overall but caution against DR integration exclusively within baseload generators’ portfolios due to limited market benefits.
{"title":"Demand response control structure in imperfectly competitive power markets: Independent or integrated?","authors":"Julien Ancel","doi":"10.1016/j.eneco.2026.109195","DOIUrl":"10.1016/j.eneco.2026.109195","url":null,"abstract":"<div><div>This article investigates different types of actors controlling demand response (DR) operations under Cournot competition. Analytical results linking shiftable load level, market equilibrium, and welfare are obtained for DR operated either by an independent aggregator (price-taker or price-maker), by end-consumers’ suppliers, or within the portfolio of generators. An application to a 2035 French power system with detailed flexible appliances constraints is also proposed. Results show that supplier-integrated DR yields the greatest price reductions and lowest shiftable load withholding, while DR integrated with baseload producers has the weakest effects on prices and may worsen welfare losses compared to a perfectly competitive market. While DR deployment consistently improves welfare and lowers prices, the extent depends on the control structure. Independent aggregation and supplier integration deliver similar welfare gains but shift surplus toward consumers, whereas integration within generators results in up to a 6€/MWh higher producer surplus compared to the other structures. Policy implications highlight the importance of DR deployment overall but caution against DR integration exclusively within baseload generators’ portfolios due to limited market benefits.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109195"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146160352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-27DOI: 10.1016/j.eneco.2026.109169
Shamim Homaei , Simon Roussanaly , Asgeir Tomasgard
This paper examines the roles of long-run and short-run marginal costs (LRMC and SRMC) in shaping electricity prices and ensuring investment cost recovery, particularly when generation capacity is used across multiple long-term periods. Using a stylized capacity expansion model with two generators and two periods, we developed a five-step methodology to characterize all possible LRMC pricing profiles and prove cost recovery under each case. We showed how shared capacity affects intertemporal cost allocation, revealing that even when cheaper technologies are marginal, more expensive shared capacity can still recover its cost through distribution across periods. On the SRMC side, we identified a form of degeneracy caused by fixed invested capacities, leading to multiple valid marginal prices. To resolve price degeneracy, we add a small demand elasticity centered on the LRMC reference point. This yields a unique SRMC price that coincides with LRMC and guarantees cost recovery under energy-only pricing. Extensions to the model, such as increasing temporal resolution, adding storage, or including more generators, demonstrated the robustness of our findings.
{"title":"Analysis of short-run and long-run marginal costs of electricity generation in the power market","authors":"Shamim Homaei , Simon Roussanaly , Asgeir Tomasgard","doi":"10.1016/j.eneco.2026.109169","DOIUrl":"10.1016/j.eneco.2026.109169","url":null,"abstract":"<div><div>This paper examines the roles of long-run and short-run marginal costs (LRMC and SRMC) in shaping electricity prices and ensuring investment cost recovery, particularly when generation capacity is used across multiple long-term periods. Using a stylized capacity expansion model with two generators and two periods, we developed a five-step methodology to characterize all possible LRMC pricing profiles and prove cost recovery under each case. We showed how shared capacity affects intertemporal cost allocation, revealing that even when cheaper technologies are marginal, more expensive shared capacity can still recover its cost through distribution across periods. On the SRMC side, we identified a form of degeneracy caused by fixed invested capacities, leading to multiple valid marginal prices. To resolve price degeneracy, we add a small demand elasticity centered on the LRMC reference point. This yields a unique SRMC price that coincides with LRMC and guarantees cost recovery under energy-only pricing. Extensions to the model, such as increasing temporal resolution, adding storage, or including more generators, demonstrated the robustness of our findings.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"155 ","pages":"Article 109169"},"PeriodicalIF":14.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}