Sustainable Energy Grids & Networks最新文献

英文中文

Modeling and operational analysis of ship integrated energy system considering partial-load characteristics of equipment and transferable loads

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-11 DOI: 10.1016/j.segan.2025.101651

Xiaolei Jiang , Zhen Xu , Yingchun Xie , Hao Wang , Haoxun Yuan , Jin Qin

The rapid development of the shipping industry has brought serious energy consumption and environmental pollution issues. Efficient management of the Ship Integrated Energy System (S-IES) has become a critical necessity to promote the sustainable development of the shipping industry. Compared to onshore system, S-IES faces more complex and unstable equipment conditions and load demands, requiring more flexible and reliable system operational strategy. Energy Hub (EH) is an effective and versatile modeling method. In this study, a dynamic EH model considering partial-load characteristics of equipment and transferable loads is established. Using a cruise ship as an application case, the load scheduling schemes for different seasons are analyzed, and the results for three scenarios in each season are compared to validate the model's effectiveness. The results show that accounting for the partial-load characteristics of equipment enhances the accuracy of the system model. Introducing transferable loads improves the operational performance of the system. Compared to the scenarios considering only the partial-load characteristics of equipment, the scenarios that also include transferable loads reduce daily operating costs by 1.61 %, 1.03 %, and 2.05 %, and relatively increase the primary energy utilization rates by 1.87 %, 0.91 %, and 2.16 % in summer, mid-season, and winter, respectively.

{"title":"Modeling and operational analysis of ship integrated energy system considering partial-load characteristics of equipment and transferable loads","authors":"Xiaolei Jiang , Zhen Xu , Yingchun Xie , Hao Wang , Haoxun Yuan , Jin Qin","doi":"10.1016/j.segan.2025.101651","DOIUrl":"10.1016/j.segan.2025.101651","url":null,"abstract":"<div><div>The rapid development of the shipping industry has brought serious energy consumption and environmental pollution issues. Efficient management of the Ship Integrated Energy System (S-IES) has become a critical necessity to promote the sustainable development of the shipping industry. Compared to onshore system, S-IES faces more complex and unstable equipment conditions and load demands, requiring more flexible and reliable system operational strategy. Energy Hub (EH) is an effective and versatile modeling method. In this study, a dynamic EH model considering partial-load characteristics of equipment and transferable loads is established. Using a cruise ship as an application case, the load scheduling schemes for different seasons are analyzed, and the results for three scenarios in each season are compared to validate the model's effectiveness. The results show that accounting for the partial-load characteristics of equipment enhances the accuracy of the system model. Introducing transferable loads improves the operational performance of the system. Compared to the scenarios considering only the partial-load characteristics of equipment, the scenarios that also include transferable loads reduce daily operating costs by 1.61 %, 1.03 %, and 2.05 %, and relatively increase the primary energy utilization rates by 1.87 %, 0.91 %, and 2.16 % in summer, mid-season, and winter, respectively.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101651"},"PeriodicalIF":4.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422666","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

False data injection to conceal load-altering attacks via electric vehicles

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-10 DOI: 10.1016/j.segan.2025.101640

Beheshteh Raouf , Seyedamirabbas Mousavian

Vehicle-to-grid (V2G) technology offers promising solutions for enhancing power systems stability and controllability by utilizing electric vehicles as flexible energy resources. Despite these advantages, the V2G technology can also expose the power system’s security and normal operation to new threats. The risks of a novel attack strategy were investigated where a false data injection attack was used to conceal a load-altering attack through electric vehicle charging stations. Scenarios where an attacker has different levels of knowledge about the system were considered. In the ideal scenario for an attacker where full system knowledge is available, the attack involved a Jacobian method to identify the most vulnerable buses. Chi-squared and maximum normalized residual tests were used to assess the attack success. It was shown that successful attacks causing voltage and frequency instabilities are possible even when the attacker has partial knowledge of the system.

引用次数: 0

Proof of Collaborative Contribution — A consensus protocol that incentivizes contribution with applications to distributed solar energy generation

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-10 DOI: 10.1016/j.segan.2025.101641

Damilare Peter Oyinloye , Je Sen Teh , Mohd Najwadi Yusoff

Blockchain technology has been adopted in various sectors including health, energy and agriculture. It functions as a distributed ledger maintained by multiple nodes, relying on consensus protocols to verify transactions and reach agreement. However, conventional protocols like Proof of Work (PoW) and Proof of Stake (PoS) face challenges with scalability and energy efficiency. This paper introduces Proof of Collaborative Contribution (PoCC), a new consensus protocol aimed at encouraging positive network contributions and fostering collaboration. It utilizes a simplified hashing mechanism secured by trusted execution environments (TEEs). As a proof of concept, PoCC is applied to a solar energy generation system, where prosumers are incentivized to offset their energy consumption and feed excess energy back into the grid. Using real-world energy data from AusGrid, our simulations demonstrate that PoCC ensures equitable block leader selection. We also show that PoCC scales well with the number of nodes, consumes significantly less energy than PoW, and is resistant to Sybil and 51% attacks. We also briefly explore other potential applications of PoCC in systems that aim to reward node contributions.

{"title":"Proof of Collaborative Contribution — A consensus protocol that incentivizes contribution with applications to distributed solar energy generation","authors":"Damilare Peter Oyinloye , Je Sen Teh , Mohd Najwadi Yusoff","doi":"10.1016/j.segan.2025.101641","DOIUrl":"10.1016/j.segan.2025.101641","url":null,"abstract":"<div><div>Blockchain technology has been adopted in various sectors including health, energy and agriculture. It functions as a distributed ledger maintained by multiple nodes, relying on consensus protocols to verify transactions and reach agreement. However, conventional protocols like Proof of Work (PoW) and Proof of Stake (PoS) face challenges with scalability and energy efficiency. This paper introduces Proof of Collaborative Contribution (PoCC), a new consensus protocol aimed at encouraging positive network contributions and fostering collaboration. It utilizes a simplified hashing mechanism secured by trusted execution environments (TEEs). As a proof of concept, PoCC is applied to a solar energy generation system, where prosumers are incentivized to offset their energy consumption and feed excess energy back into the grid. Using real-world energy data from AusGrid, our simulations demonstrate that PoCC ensures equitable block leader selection. We also show that PoCC scales well with the number of nodes, consumes significantly less energy than PoW, and is resistant to Sybil and 51% attacks. We also briefly explore other potential applications of PoCC in systems that aim to reward node contributions.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101641"},"PeriodicalIF":4.8,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387966","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

Network-aware MILP model for scheduling multi-energy systems considering carbon emissions and customers’ satisfaction: A DRCC approach

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-10 DOI: 10.1016/j.segan.2025.101636

Shuguang Li , Yongfeng Wang , Ali Jawad Alrubaie , Mohamed Salem , Mohammed Sh. Majid , Rasheed Abdulkader

The rapid growth of multi-energy systems (MESs) with electricity, natural gas, and heat generations and conversions necessitates efficient management frameworks to harness the offered flexibility by the system components. This paper proposes a mixed-integer linear programming (MILP) model to optimally manage a MES equipped with electric vehicle (EV) charging stations, combined heat and power (CHP) units, renewable energy sources (RESs), energy storage systems, and electric heat pumps. The objective function of the problem is to minimize the operation cost of MES, which includes the cost of purchased energy from the external electricity and gas networks, the cost of carbon emissions, and the penalty to compensate for the dissatisfaction of households and EV owners. The constraints of the electricity grid and natural gas network are incorporated into the proposed energy management scheme using the linearized AC power flow and gas flow equations. Moreover, the uncertainties associated with RESs and demand are modeled using the distributionally robust chance-constrained (DRCC) approach to not only guarantee the robustness of the optimal scheduling plan against uncertainties, but also incorporate the probabilistic nature of these uncertain parameters. Finally, the IEEE 33-bus electricity grid and 14-node gas network are employed to validate the effectiveness and applicability of the presented methodology from the viewpoints of the system operator and customers.

{"title":"Network-aware MILP model for scheduling multi-energy systems considering carbon emissions and customers’ satisfaction: A DRCC approach","authors":"Shuguang Li , Yongfeng Wang , Ali Jawad Alrubaie , Mohamed Salem , Mohammed Sh. Majid , Rasheed Abdulkader","doi":"10.1016/j.segan.2025.101636","DOIUrl":"10.1016/j.segan.2025.101636","url":null,"abstract":"<div><div>The rapid growth of multi-energy systems (MESs) with electricity, natural gas, and heat generations and conversions necessitates efficient management frameworks to harness the offered flexibility by the system components. This paper proposes a mixed-integer linear programming (MILP) model to optimally manage a MES equipped with electric vehicle (EV) charging stations, combined heat and power (CHP) units, renewable energy sources (RESs), energy storage systems, and electric heat pumps. The objective function of the problem is to minimize the operation cost of MES, which includes the cost of purchased energy from the external electricity and gas networks, the cost of carbon emissions, and the penalty to compensate for the dissatisfaction of households and EV owners. The constraints of the electricity grid and natural gas network are incorporated into the proposed energy management scheme using the linearized AC power flow and gas flow equations. Moreover, the uncertainties associated with RESs and demand are modeled using the distributionally robust chance-constrained (DRCC) approach to not only guarantee the robustness of the optimal scheduling plan against uncertainties, but also incorporate the probabilistic nature of these uncertain parameters. Finally, the IEEE 33-bus electricity grid and 14-node gas network are employed to validate the effectiveness and applicability of the presented methodology from the viewpoints of the system operator and customers.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101636"},"PeriodicalIF":4.8,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387963","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

A novel power flow approach for calculating the steady-state of secondary control in islanded microgrids under cyberattacks

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-08 DOI: 10.1016/j.segan.2025.101646

Evangelos E. Pompodakis, Georgios I. Orfanoudakis, Giannis Katsigiannis, Antonios Tsikalakis, Emmanuel Karapidakis

Under ideal conditions, state-of-the-art methods for computing the power flow of islanded microgrids (MGs) are adequate for estimating the steady-state of the MG. However, this paper demonstrates that cyberattacks targeting the secondary control of the MG can significantly alter the power and frequency of the MG. In such scenarios, these traditional methods fall short, as they do not incorporate the effects of secondary control actions. To address this limitation, this paper proposes a novel power flow formulation incorporating secondary control equations of MGs under cyberattacks. The resulting system is a nonlinear mathematical model, solvable using standard nonlinear solvers such as the Newton Trust Region method. This proposed formulation significantly advances conventional power flow analysis by enabling, for the first time, the computation of steady-state impacts of cyberattacks on the secondary control of islanded MGs. Simulations conducted on 6-bus and 12-bus islanded MGs confirm that the results of the proposed approach match those of Simulink, demonstrating the high accuracy of the method. Moreover, they underscore the advancements of the proposed approach compared to the standard power flow methods traditionally used for steady-state modeling of islanded MGs.

{"title":"A novel power flow approach for calculating the steady-state of secondary control in islanded microgrids under cyberattacks","authors":"Evangelos E. Pompodakis, Georgios I. Orfanoudakis, Giannis Katsigiannis, Antonios Tsikalakis, Emmanuel Karapidakis","doi":"10.1016/j.segan.2025.101646","DOIUrl":"10.1016/j.segan.2025.101646","url":null,"abstract":"<div><div>Under ideal conditions, state-of-the-art methods for computing the power flow of islanded microgrids (MGs) are adequate for estimating the steady-state of the MG. However, this paper demonstrates that cyberattacks targeting the secondary control of the MG can significantly alter the power and frequency of the MG. In such scenarios, these traditional methods fall short, as they do not incorporate the effects of secondary control actions. To address this limitation, this paper proposes a novel power flow formulation incorporating secondary control equations of MGs under cyberattacks. The resulting system is a nonlinear mathematical model, solvable using standard nonlinear solvers such as the Newton Trust Region method. This proposed formulation significantly advances conventional power flow analysis by enabling, for the first time, the computation of steady-state impacts of cyberattacks on the secondary control of islanded MGs. Simulations conducted on 6-bus and 12-bus islanded MGs confirm that the results of the proposed approach match those of Simulink, demonstrating the high accuracy of the method. Moreover, they underscore the advancements of the proposed approach compared to the standard power flow methods traditionally used for steady-state modeling of islanded MGs.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101646"},"PeriodicalIF":4.8,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387964","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

Coordinated operational optimization of water and power systems under emergency conditions

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-07 DOI: 10.1016/j.segan.2025.101643

Gal Perelman , Tomer Shmaya , Aviad Navon , Stelios Vrachimis , Mathaios Panteli , Demetrios G. Eliades , Avi Ostfeld

This research addresses the integrated management of Water Distribution Systems (WDS) and Power Distribution Systems (PDS) to enhance operational efficiency and resilience during extreme scenarios. Traditionally, these systems are operated independently, leading to sub-optimal performance. Alternatively, some studies have proposed a joint operation of WDS and PDS, assuming that decisions are made simultaneously by a single decision-maker, which is impractical. We propose a novel emergency control method that relies on sparse communication between WDS and PDS operators, aiming to minimize load shedding (LS) in the PDS by strategically managing power demand in the interconnected WDS. The results show that the proposed coordinated approach has similar performance to a full cooperation approach between the two systems while requiring only minimal information exchange. Our approach demonstrates the potential of limited yet targeted information exchange, fostering cross-sectoral collaboration to maintain service continuity under extreme conditions, and underscores the critical role of integrated management in ensuring the resilience of interconnected infrastructure systems.

{"title":"Coordinated operational optimization of water and power systems under emergency conditions","authors":"Gal Perelman , Tomer Shmaya , Aviad Navon , Stelios Vrachimis , Mathaios Panteli , Demetrios G. Eliades , Avi Ostfeld","doi":"10.1016/j.segan.2025.101643","DOIUrl":"10.1016/j.segan.2025.101643","url":null,"abstract":"<div><div>This research addresses the integrated management of Water Distribution Systems (WDS) and Power Distribution Systems (PDS) to enhance operational efficiency and resilience during extreme scenarios. Traditionally, these systems are operated independently, leading to sub-optimal performance. Alternatively, some studies have proposed a joint operation of WDS and PDS, assuming that decisions are made simultaneously by a single decision-maker, which is impractical. We propose a novel emergency control method that relies on sparse communication between WDS and PDS operators, aiming to minimize load shedding (LS) in the PDS by strategically managing power demand in the interconnected WDS. The results show that the proposed coordinated approach has similar performance to a full cooperation approach between the two systems while requiring only minimal information exchange. Our approach demonstrates the potential of limited yet targeted information exchange, fostering cross-sectoral collaboration to maintain service continuity under extreme conditions, and underscores the critical role of integrated management in ensuring the resilience of interconnected infrastructure systems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101643"},"PeriodicalIF":4.8,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378243","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

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 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-06 DOI: 10.1016/j.segan.2025.101634

Pouya Salyani , Kazem Zare , Tuba Gözel

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.

{"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 Q2 ENERGY & FUELS

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

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.

{"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 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-05 DOI: 10.1016/j.segan.2025.101642

Fawzy A. Bukhari, Khalid A. Alnowibet

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 min-max-min structures. A conventional RTCUC problem is formulated as a min-max-min 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 min-max-min 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 min-max-min-max-min 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.

{"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 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2025-02-05 DOI: 10.1016/j.segan.2025.101647

Chao Qin, Xu Hu, Chongyu Zhong, Yuan Zeng

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.

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