Energy Conversion and Economics最新文献_第4页

Energy Conversion and Economics Pub Date : 2026-02-13

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Energy Conversion and Economics Pub Date : 2026-02-12

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Energy Conversion and Economics Pub Date : 2026-02-12

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Energy Conversion and Economics Pub Date : 2026-02-05

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Energy Conversion and Economics Pub Date : 2026-02-05

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Locational marginal capacity pricing for power system resilience 电力系统弹性的区位边际容量定价

Energy Conversion and Economics Pub Date : 2025-12-25 Epub Date: 2025-12-15 DOI: 10.1049/enc2.70025

Yunpeng Xiao, Yuerong Zhu, Ying Qu, Jin Zhao, Haipeng Xie, Xiuli Wang, Xifan Wang

{"title":"Locational marginal capacity pricing for power system resilience","authors":"Yunpeng Xiao, Yuerong Zhu, Ying Qu, Jin Zhao, Haipeng Xie, Xiuli Wang, Xifan Wang","doi":"10.1049/enc2.70025","DOIUrl":"10.1049/enc2.70025","url":null,"abstract":"As the industry shifts towards smarter and greener power systems, enhancing the resilience of power systems against increasingly frequent extreme events has become an urgent priority that requires substantial investment. Therefore, effectively quantifying the value of resilience resources (i.e. the resources contributing to improved resilience) and providing transparent economic signals to incentivize their deployment poses a critical challenge. Inspired by locational marginal pricing for energy and capacity, this study proposes a methodology for locational marginal capacity pricing for power system resilience. We first evaluated power system resilience and generated pricing scenarios using a robust optimization approach. The resulting resilience prices reflect the marginal contribution of the maximum capacity of resilience resources to the overall resilience enhancement. During extreme events, resilient resources receiving revenues are obligated to ensure their availability, whereas customers paying fees gain pre-event resilience commitments and priority in load restoration. The case studies validate the effectiveness of the proposed resilience pricing, demonstrating its ability to capture node-specific demands for resilience resources and quantify their value in enhancing system-wide resilience. Moreover, the resilience price provides a transparent and effective economic signal to guide the optimal location and sizing of resilience resources, as well as inform line hardening and expansion strategies.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 6","pages":"410-421"},"PeriodicalIF":0.0,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Data-driven long-term wind speed forecasting and techno-economics of offshore wind-to-hydrogen production 数据驱动的长期风速预测和海上风能制氢的技术经济

Energy Conversion and Economics Pub Date : 2025-12-25 Epub Date: 2025-12-18 DOI: 10.1049/enc2.70029

Prihandono Aditama, Abdul Wasy Zia

{"title":"Data-driven long-term wind speed forecasting and techno-economics of offshore wind-to-hydrogen production","authors":"Prihandono Aditama, Abdul Wasy Zia","doi":"10.1049/enc2.70029","DOIUrl":"10.1049/enc2.70029","url":null,"abstract":"The economic viability of offshore wind-to-hydrogen systems depends heavily on the accuracy of wind-speed forecasting. We evaluated three probabilistic scenario generators (historical bootstrapping, parametric Weibull fitting, and calibrated long short-term memory (LSTM) sequence model) using a decision-coupled framework. From 61 years of ERA5, we created 1000 synthetic 23-year hourly scenarios per method, propagated them through a techno-economic model, and scored the continuous ranked probability score (CRPS) on economic distributions (levelized cost of hydrogen (LCOH), net present value (NPV), and interest rate of return (IRR)). We report the decision bandwidth and its elasticity to skill, and run a financing price sweep to meet probability targets. Relative to bootstrapping and Weibull, the LSTM lowers CRPS by 30% for LCOH and NPV (25% for IRR), narrowing risk bands at similar medians. The hydrogen price required to reach more than 90% probability is €7.76–7.78/kg for Pr(NPV > 0) and €9.16-9.18/kg for Pr(NPV > 0 and IRR > 10%). A cross-method spread of less than €0.02/kg indicates a threshold-saturated regime, in which better skills mainly contract risk. Robustness tests shift medians, but preserve method ranking and thresholds. This framework translates probabilistic forecasting skills into finance ability metrics for wind-to-hydrogen screening and policy design.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 6","pages":"388-409"},"PeriodicalIF":0.0,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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TransSense: A multilevel attention and rotary positional embedding-based transformer for load disaggregation TransSense：基于多级关注和旋转位置嵌入的负载分解变压器

Energy Conversion and Economics Pub Date : 2025-12-25 Epub Date: 2025-12-17 DOI: 10.1049/enc2.70028

Lei Jiang, Huan Liu, Jesse S. Jin, Yu Zheng, Xin He, Jie Zhao

{"title":"TransSense: A multilevel attention and rotary positional embedding-based transformer for load disaggregation","authors":"Lei Jiang, Huan Liu, Jesse S. Jin, Yu Zheng, Xin He, Jie Zhao","doi":"10.1049/enc2.70028","DOIUrl":"10.1049/enc2.70028","url":null,"abstract":"Non-intrusive load monitoring (NILM) aims to decompose total electricity usage into appliance-specific signals, facilitating detailed energy management without the need for further hardware installation. However, precisely isolating the consumption of specific appliances remains difficult because of overlapping signatures, transient fluctuations, and noise interference. In this study, we propose TransSense as a transformer-based NILM framework designed to overcome these challenges by using multiscale feature extraction and improved temporal modelling. TransSense integrates global and local attention processes to capture both long-term consumption trends and short-term switching events to balance comprehensive contextual comprehension with resilience to localized noise. The model incorporates rotary positional embeddings to capture relative temporal connections in energy consumption patterns. This approach dramatically enhances sequential sensitivity compared to conventional absolute positional encoding. We also implement a hierarchical feature extraction module that includes pooling operations and transformer blocks to reduce redundancy and enhance significant temporal features across various time scales. The results of an extensive experimental evaluation on the Reference Energy Disaggregation Data Set (REDD) and UK Domestic Appliance-Level Electricity (UK-Dale) datasets show that the TransSense model performed better than the conventional benchmark methods used for comparison. These results reflect its enhanced predictive accuracy, robust identification of different load states, and strong resilience to noise. Our findings underscore TransSense's potential as a scalable and generalizable solution for intelligent energy disaggregation on future smart grid infrastructure.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 6","pages":"371-387"},"PeriodicalIF":0.0,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Multi-agent deep reinforcement learning-enabled voltage regulation approach for partitioned active distribution network using heterogeneous PV inverters 基于多智能体深度强化学习的异构光伏逆变器分区有源配电网电压调节方法

Energy Conversion and Economics Pub Date : 2025-12-25 Epub Date: 2025-12-12 DOI: 10.1049/enc2.70026

Kang Xiong, Chengjin Ye, Bin Liu, Xun Suo

{"title":"Multi-agent deep reinforcement learning-enabled voltage regulation approach for partitioned active distribution network using heterogeneous PV inverters","authors":"Kang Xiong, Chengjin Ye, Bin Liu, Xun Suo","doi":"10.1049/enc2.70026","DOIUrl":"10.1049/enc2.70026","url":null,"abstract":"To improve the adaptability of voltage regulation in active distribution networks (ADNs) with high photovoltaic (PV) penetration, this paper proposes a distributed Volt/Var control (VVC) strategy enabled by multi-agent deep reinforcement learning and implemented through heterogeneous PV inverters. First, a distributed VVC framework is established by partitioning the ADN into multiple sub-networks, each modelled as an agent, with the goal of minimizing voltage deviation. This control framework considers the heterogeneous operation modes of PV systems and utilizes both reactive power support and active power curtailment to maintain voltage within acceptable limits. Then, the VVC problem is formulated as a Markov game and solved using a multi-agent soft actor–critic algorithm. Simulation studies conducted on the IEEE 33-bus and 118-bus test systems validated the effectiveness of the proposed method, demonstrating its superior performance in reducing voltage fluctuations compared to benchmark approaches.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 6","pages":"359-370"},"PeriodicalIF":0.0,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Wide-area damping control in renewable integrated power systems: A review on recent achievements and new challenges 可再生综合电力系统的广域阻尼控制：新进展与新挑战

Energy Conversion and Economics Pub Date : 2025-12-25 Epub Date: 2025-12-15 DOI: 10.1049/enc2.70027

Linglin Meng, Haixin Wang, Shengyang Lu, Zihao Yang, Zhe Chen, Hassan Bevrani, Sharara Rehimi, Mingchao Xia, Dan Doru Micu, Fausto Pedro García Márquez, Junyou Yang

{"title":"Wide-area damping control in renewable integrated power systems: A review on recent achievements and new challenges","authors":"Linglin Meng, Haixin Wang, Shengyang Lu, Zihao Yang, Zhe Chen, Hassan Bevrani, Sharara Rehimi, Mingchao Xia, Dan Doru Micu, Fausto Pedro García Márquez, Junyou Yang","doi":"10.1049/enc2.70027","DOIUrl":"10.1049/enc2.70027","url":null,"abstract":"Low-frequency oscillations (LFOs) remain a major obstacle to maintaining stable dynamic performance in power systems with high levels of renewable energy integration. In particular, inter-area LFOs have emerged as a critical concern in large, interconnected grids. In recent years, wide-area damping control (WADC) has been widely studied in suppressing inter-area LFOs in power systems with renewable energy. This paper provides a comprehensive review of the key technologies underpinning WADC within the framework of wide-area measurement systems. First, it outlines the overall structure of WADC in renewable-integrated power systems. Next, it examines the central technical issues associated with WADC in detail. The paper then summarizes and compares various offline and online adaptive design methodologies for wide-area damping controllers. Finally, it discusses the major challenges facing WADC and highlights future development opportunities. Overall, this review aims to deliver a thorough and meaningful overview of current research on WADC for power systems with high renewable energy penetration.","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 6","pages":"341-358"},"PeriodicalIF":0.0,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0