Sustainable Energy Grids & Networks最新文献_第2页

Proactive scheduling of transactive multi-carrier microgrids under base interruptible program: A Bi-level model approach

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-06 DOI: 10.1016/j.segan.2025.101634

Pouya Salyani , Kazem Zare , Tuba Gözel

{"title":"Proactive scheduling of transactive multi-carrier microgrids under base interruptible program: A Bi-level model approach","authors":"Pouya Salyani , Kazem Zare , Tuba Gözel","doi":"10.1016/j.segan.2025.101634","DOIUrl":"10.1016/j.segan.2025.101634","url":null,"abstract":"<div><div>Power systems are susceptible to disruptions caused by natural disasters, leading to significant financial losses for distribution companies. The versatility of multi-carrier microgrids (MCMGs) in meeting the needs of various carriers, such as electricity and heat, has garnered considerable interest. The focus of this paper is on how transactive multi-carrier microgrids (TMCM) contribute to improving the resilience of energy systems during prolonged outages. A bi-level proactive day-ahead scheduling model of TMCMs is introduced herein that not only achieves optimal normal operation cost, but also ensures the maximum demand serving of power, heat, gas and hydrogen carriers during outages. The base interruptible program (BIP) ensures a successful and economically efficient way to ride through outage conditions, serving as an emergency demand response resource for the TMCM. Furthermore, each MCMG has its designated 24-hour marginal price that enables the power transaction among the MCMGs at both the normal and outage condition. The bi-level model is converted into a single-level scheduling model by applying the Karush-Kuhn-Tucker (KKT) condition. This approach utilizes a two-stage reformulation method to handle the integer variables. The simulation reveals that the need to sell power from MCMG 1 during the outage period has led to the supply of electricity in the market for six hours during peak time. Despite the only-power operation mode in five hours of the possible outage period, due to the high thermal load of microgrid 1, one of the CHP units is dispatched to produce 50–100 kW in cogeneration mode at 11:00–13:00.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101634"},"PeriodicalIF":4.8,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive optimization and dynamic pricing in decentralized energy markets using blockchain technology and consensus-based verification

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-06 DOI: 10.1016/j.segan.2025.101630

Nishkar R. Naraindath , Raj M. Naidoo , Ramesh C. Bansal

{"title":"Adaptive optimization and dynamic pricing in decentralized energy markets using blockchain technology and consensus-based verification","authors":"Nishkar R. Naraindath , Raj M. Naidoo , Ramesh C. Bansal","doi":"10.1016/j.segan.2025.101630","DOIUrl":"10.1016/j.segan.2025.101630","url":null,"abstract":"<div><div>Peer-to-peer (P2P) markets are the key to unlocking the streamlined convergence of the prominent 5D elements in microgrids. However, current implementations focus on conventional methods that prioritize electricity cost reduction which often results in sub-optimal grid operation. This underscores the need for holistic and adaptive optimization in decentralized energy markets. This research introduces a novel consensus strategy built on principles from blockchains to serve as an overarching cross-verification tool that ensures integrity between off-chain and on-chain computations. The strategy leverages a dynamic stake function and reputation system to outperform traditional proof-of-stake. An adaptive optimization model along with a dynamic pricing model is then proposed and validated through multiple Python simulations. The work is proven to improve P2P interactions and grid efficiency. Furthermore, the overall system was implemented in a Solidity smart contract and deployed on an Ethereum test work to demonstrate the interoperability and functionality of the framework proposed. Suggestions for subsequent research are additionally included. In summary, this paper contributes to decentralized, equitable, efficient and self-sufficient microgrids.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101630"},"PeriodicalIF":4.8,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust transmission-constrained unit commitment considering robust economic redispatch: A tri-stage five-level structure

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-05 DOI: 10.1016/j.segan.2025.101642

Fawzy A. Bukhari, Khalid A. Alnowibet

{"title":"Robust transmission-constrained unit commitment considering robust economic redispatch: A tri-stage five-level structure","authors":"Fawzy A. Bukhari, Khalid A. Alnowibet","doi":"10.1016/j.segan.2025.101642","DOIUrl":"10.1016/j.segan.2025.101642","url":null,"abstract":"<div><div>Integrating renewable energy sources (RESs) into power systems increases operational uncertainty and threatens their efficiency. Hence, it is imperative to devise effective techniques to handle the uncertainty and mitigate the variability impacts of RESs in a transmission-constrained unit commitment (TCUC) problem. We propose a novel robust TCUC (RTCUC) model considering the robust economic redispatch (RERD) problem (balancing problem). To this end, a tri-stage, five-level hierarchical framework is constructed with two successive <em>min-max-min</em> structures. A conventional RTCUC problem is formulated as a <em>min-max-min</em> problem where the first stage decides on commitment statuses, and the second stage determines the generation scheduling using an economic dispatch model. In this paper, we change this conventional model by revisiting the second stage and formulating it as another <em>min-max-min</em> problem whose first stage determines the optimal base generation. Its second stage identifies the optimal generation re-scheduling (GRS) solution using an economic redispatch model. Thus, the whole problem is established based on a tri-stage <em>min-max-min-max-min</em> structure. The proposed problem is solved using the nested primal Benders decomposition (PBD) algorithm. The numerical studies reveal the outperformance of the proposed RTCUC model over the conventional models.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101642"},"PeriodicalIF":4.8,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vulnerability analysis of power system under uncertain cyber-physical attacks based on stochastic bi-level optimization

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-05 DOI: 10.1016/j.segan.2025.101647

Chao Qin, Xu Hu, Chongyu Zhong, Yuan Zeng

{"title":"Vulnerability analysis of power system under uncertain cyber-physical attacks based on stochastic bi-level optimization","authors":"Chao Qin, Xu Hu, Chongyu Zhong, Yuan Zeng","doi":"10.1016/j.segan.2025.101647","DOIUrl":"10.1016/j.segan.2025.101647","url":null,"abstract":"<div><div>Coordinated cyber-physical attacks on power systems have become increasingly prevalent, highlighting the need to explore the interactions between cyber attacks targeting relay protection and physical attacks on electrical equipment. However, existing research has yet not adequately addressed the uncertainty associated with the success probability of such attacks. This paper proposes a vulnerability analysis method of power transmission system under uncertain cyber-physical attacks based on stochastic bi-level optimization. An analytical model is developed to characterize the relationships among attack target selection, attack success/failure scenarios, and scenarios probabilities. Based on this analytical model, a stochastic bi-level optimization-based vulnerability identification model is proposed, which incorporates the success probabilities of cyber attacks and the comprehensive loss across different scenarios. Through dual decomposition and two linearization methods, the original bi-level nonlinear model is transformed into a single-level mixed-integer linear programming problem to improve the solution performance. A case study finally validates that the introduction of attack success probability parameters may lead to new attack patterns. The proposed method provides valuable insights into the attack strategies of adversaries with varying levels of capability, thereby offering a foundation for the development of effective defensive strategies.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101647"},"PeriodicalIF":4.8,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Contrastive learning for efficient anomaly detection in electricity load data

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-05 DOI: 10.1016/j.segan.2025.101639

Mohit Choubey, Rahul Kumar Chaurasiya, J.S. Yadav

{"title":"Contrastive learning for efficient anomaly detection in electricity load data","authors":"Mohit Choubey, Rahul Kumar Chaurasiya, J.S. Yadav","doi":"10.1016/j.segan.2025.101639","DOIUrl":"10.1016/j.segan.2025.101639","url":null,"abstract":"<div><div>Identifying irregularities in electricity load data is essential for maintaining dependable and effective power systems. Traditional approaches necessitate a significant amount of labeled data in order to achieve high accuracy, resulting in increased costs, and limited scalability. This paper introduces a feature extraction model based on contrastive learning, which greatly enhances the accuracy of anomaly detection for electricity load data. The model generates both positive and negative pairs after utilizing original input data sequences. This enables to learn complex similarities and differences. Through the utilization of a contrastive loss function, the aim is to minimize disparities between positive pairs and maximize the distances between negative pairs, resulting in the extraction of essential feature representations. The results demonstrate significant improvements enhancements such as accuracy rose from 69.85 % to 95.65 %, precision improved from 61.2 % to 96 %, recall increased from 74.5 % to 93 %, and the F1-score saw an improvement from 67.3 % to 94.6 %. The ROC-AUC score rose from 0.7286 to 0.9532, indicating better differentiation between normal and anomalous data. A paired t-test confirmed these gains with p-values well below 0.05, further validating the model’s effectiveness, while Cohen's d test validated the practical significance, indicating large effect sizes across all metrics. Furthermore, 95 % confidence intervals for the mean differences confirmed that the improvements are both statistically and practically meaningful. This approach not only improves detection accuracy but also reduces reliance on large labeled datasets, making it more scalable and cost-effective for real-world applications.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101639"},"PeriodicalIF":4.8,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal scheduling of combined air conditioner and fresh air system for price-based demand response

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-05 DOI: 10.1016/j.segan.2025.101637

Yu-Qing Bao , Xiao-Rui Song , Hui-Ling Su , Zhou-Chen Yu , Qing-He Sun , Zhong-Dong Wang

{"title":"Optimal scheduling of combined air conditioner and fresh air system for price-based demand response","authors":"Yu-Qing Bao , Xiao-Rui Song , Hui-Ling Su , Zhou-Chen Yu , Qing-He Sun , Zhong-Dong Wang","doi":"10.1016/j.segan.2025.101637","DOIUrl":"10.1016/j.segan.2025.101637","url":null,"abstract":"<div><div>It is well known that energy management of air conditioners (ACs) is an important way of demand response (DR). The fresh air system (FAS), which is another common equipment in buildings, can effectively utilize cooling capacity of the outdoor air during the night to reduce indoor temperatures, achieving energy savings and efficiency. However, the combined scheduling of AC and FAS has received little attention. In this paper, a co-optimization scheduling method for combined AC and fresh air system (ACFAS) is proposed. Building upon the thermodynamic models of AC and FAS and considering the practical conditions, the main-power ON/OFF state, temperature set-point, and air volume level of the AC and FAS are selected as decision variables to establish a thermostatic control model. The thermostatic control model is then discretized and linearized to form a mixed-integer linear programming solvable format. Subsequently, taking into account electricity cost and comfort objectives, an optimization scheduling model is developed, allowing for the determination of the scheduling results of the main power ON/OFF state, temperature set-point, and air volume level. The testing results show that the co-optimization can utilize both AC and FAS for cooling the room temperature, and the energy efficiency can be improved.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101637"},"PeriodicalIF":4.8,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

New tight expression of network radiality constraints using constant commodity flow equipped with the parent–child supply chain

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-04 DOI: 10.1016/j.segan.2025.101631

Ali Alizadeh , Moein Esfahani , Bo Cao , Innocent Kamwa , Minghui Xu

{"title":"New tight expression of network radiality constraints using constant commodity flow equipped with the parent–child supply chain","authors":"Ali Alizadeh , Moein Esfahani , Bo Cao , Innocent Kamwa , Minghui Xu","doi":"10.1016/j.segan.2025.101631","DOIUrl":"10.1016/j.segan.2025.101631","url":null,"abstract":"<div><div>Preserving radiality is essential in distribution networks and Microgrid (MG) formation to ensure cost efficiency, reliability, and resiliency. However, maintaining radiality poses significant challenges due to the complexity of large-scale networks. Most existing models rely on Mixed-Integer Linear Programming (MILP) formulations, which suffer from low tightness, limiting their optimality and scalability. This paper addresses these limitations by introducing highly compact and tight radiality constraints designed to enhance computational performance and accuracy in reconfiguration and MG formation problems. The proposed approach is built on the novel Parent–Child Supply Chain (PCSC) framework, which, combined with a Constant Commodity Flow (CCF) model, ensures binary-like behavior for radiality variables without enforcing integer constraints. This innovation reduces the complexity of the problem, requiring binary variables only for line-switching decisions. Implementations of the model demonstrate significant improvements in computational performance, achieving a reduction of up to 72.61% in solution time and 14.7% in error margin compared to conventional MILP formulations. Moreover, the high tightness of the proposed constraints enables the use of second-order conic programming for highly accurate Distribution Power Flow (DistFlow) modeling. This advancement empowers operators to make realistic and informed decisions. The findings highlight the model’s potential to transform industry practices by offering a robust and scalable solution for network reconfiguration and MG formation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101631"},"PeriodicalIF":4.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143239307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Maximization of renewable generation hosting capacity in power transmission grids considering participation in energy and flexibility markets: A bilevel optimization model

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-04 DOI: 10.1016/j.segan.2025.101633

Milad Mousavi , Mahsa Azarnia , Jin Zhong , Sarah Rönnberg

{"title":"Maximization of renewable generation hosting capacity in power transmission grids considering participation in energy and flexibility markets: A bilevel optimization model","authors":"Milad Mousavi , Mahsa Azarnia , Jin Zhong , Sarah Rönnberg","doi":"10.1016/j.segan.2025.101633","DOIUrl":"10.1016/j.segan.2025.101633","url":null,"abstract":"<div><div>Investment in renewable energy generation is integral to transitioning to sustainable power and energy systems. In this regard, the concept of hosting capacity (HC) is a useful tool for renewable generation investors and system operators to identify the maximum quantity of connected renewable resources without modification or strengthening of the grid. However, a considerable part of the extant research addresses the technical requirements of the problem in distribution systems while neglecting the transmission system and market constraints. Renewable generation uptake has reduced reliance on fossil fuel-based resources in the power sector, while also demonstrating capability to address the flexibility needs of the system. This paper proposes a market-based approach for maximizing renewable generation HC in transmission systems considering both energy and flexibility markets. To this end, a bilevel optimization problem is developed to study the profitability of maximizing renewable generation HC. In the upper-level problem, an HC maximization is developed with respect to the non-negative profitability of the new generation investment. The lower-level problem addresses social welfare maximization of energy and flexibility markets in which new renewable energy generation can participate. The formulations are transferred into a single-level mixed-integer linear programming (MILP) problem to avoid the nonlinearity of the bilevel model. The proposed model is applied to a 2-bus illustrative example and the IEEE 24-bus reliability test system (RTS). The results demonstrate that renewable generation units can improve their profitability by participating in the flexibility market and thereby increase the renewable generation HC from a market perspective.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101633"},"PeriodicalIF":4.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143239306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven and physically informed power grid dispatch decision-making method

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-02-04 DOI: 10.1016/j.segan.2025.101644

Kai Sun , Dahai Zhang , Jiye Wang , Wenbo Mao

引用次数: 0

A generalized Nash-in-Nash bargaining solution to allocating energy loss and network usage cost of buildings in peer-to-peer trading market

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2025-01-30 DOI: 10.1016/j.segan.2025.101628

Yuanxing Xia , Yu Huang , Jicheng Fang

{"title":"A generalized Nash-in-Nash bargaining solution to allocating energy loss and network usage cost of buildings in peer-to-peer trading market","authors":"Yuanxing Xia , Yu Huang , Jicheng Fang","doi":"10.1016/j.segan.2025.101628","DOIUrl":"10.1016/j.segan.2025.101628","url":null,"abstract":"<div><div>Although the peer-to-peer (P2P) energy market has emerged as a promising method to accommodate the distributed energy resources (DERs) on the demand side, the different stakeholders in the market make the energy loss allocation and network usage cost problems hard to solve. Considering the inconsistent interests of various market entities, we propose a generalized Nash-in-Nash bargaining (GNNB) model for the trading result, network usage cost, and energy loss allocation in the P2P market among buildings. We first establish the profit maximization models of distribution system operators (DSO) and building managers in P2P markets. A tripartite Nash bargaining model is developed to depict the negotiation among these entities. We then equivalently transform the Nash bargaining problem into two subproblems. A nested market-clearing algorithm based on the alternating direction method of multipliers (ADMM) is developed to solve the P2P energy market equilibrium with these bargaining results. We finally import two cases to verify the effectiveness of the GNNB solution. The heterogeneous network usage prices in the GNNB solution balance the interests of DSO and building managers. It can be concluded from the numerical results that the energy losses are allocated according to market participants’ trading amounts. Therefore, the negotiation result is fair. Our proposed model presents a fair framework to determine the network cost and energy loss allocation for the P2P energy market. It can be applied to optimize the trading result and energy loss in the local energy market project. All three parties will be satisfied with this welfare distribution.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101628"},"PeriodicalIF":4.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143328124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0