To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When a...To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.展开更多
This paper proposes a co-optimal strategy using line hardening,mobile devices(mobile ice-melting device,mobile emergency generator,mobile energy storage system),and repair crew dispatching to improve distribution syst...This paper proposes a co-optimal strategy using line hardening,mobile devices(mobile ice-melting device,mobile emergency generator,mobile energy storage system),and repair crew dispatching to improve distribution system resilience during ice storms.A multi-stage defender-attacker-defender model is established to take into account interactions and coupling relationships between different measures.In our proposed model,ice storms will attack the distribution and transportation system in a worst-case scenario,affecting system performance from various perspectives.Corresponding to the different operating states in the distribution system affected by ice storms,aiming at minimizing the weighted load shedding value,this paper applies various measures to different stages to improve the response and defense capabilities to ice storms and realize restoration of the distribution system ultimately.The nested column-and-constraint generation algorithm is used to solve the model efficiently.The effectiveness of the proposed model and solution method for enhancing the distribution system resilience is verified on the modified IEEE 33-bus distribution system and modified realworld zone of Caracas 141-bus distribution system.展开更多
With the rapid integration of communication and information technology into substations,the risk of cyber attacks has significantly increased.Attackers may infiltrate substation networks,manipulate switches,and disrup...With the rapid integration of communication and information technology into substations,the risk of cyber attacks has significantly increased.Attackers may infiltrate substation networks,manipulate switches,and disrupt power lines,potentially causing severe damage to the power system.To minimize such risks,this paper proposes a three-layer defender-attacker-defender(DAD)model for optimally allocating limited defensive resources to substations.To model the uncertainty surrounding the knowledge of defender of potential attacks in realworld scenarios,we employ a fuzzy analytic hierarchy process combined with the decision-making trial and evaluation laboratory(FAHP-DEMATEL).This method accounts for the attack resource uncertainty by utilizing intelligence data on factors potentially influenced by attackers,which serves as an evaluation metric to simulate the likelihood of various attack scenarios.These uncertainty probabilities are then incorporated into the substation DAD model consisting three layers of agents:the decision-maker,the attacker,and the operator.The decision-maker devises a defense strategy before the attack,while the attacker aims to identify the strategy that causes the maximum load loss.Meanwhile,the operator seeks to minimize the load loss through optimal power flow scheduling.To solve the model,the original problem is transformed into a two-layer subproblem and a single-layer master problem,which are solved iteratively using a column-and-constraint generation algorithm.Case studies conducted on the IEEE RTS-96 system and the IEEE 118-node system demonstrate the effectiveness and practicality of the proposed model.Comparative experiments further highlight the advantages of the proposed model.展开更多
基金supported by the Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.,China (J2022160,Research on Key Technologies of Distributed Power Dispatching Control for Resilience Improvement of Distribution Networks).
文摘To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.
文摘This paper proposes a co-optimal strategy using line hardening,mobile devices(mobile ice-melting device,mobile emergency generator,mobile energy storage system),and repair crew dispatching to improve distribution system resilience during ice storms.A multi-stage defender-attacker-defender model is established to take into account interactions and coupling relationships between different measures.In our proposed model,ice storms will attack the distribution and transportation system in a worst-case scenario,affecting system performance from various perspectives.Corresponding to the different operating states in the distribution system affected by ice storms,aiming at minimizing the weighted load shedding value,this paper applies various measures to different stages to improve the response and defense capabilities to ice storms and realize restoration of the distribution system ultimately.The nested column-and-constraint generation algorithm is used to solve the model efficiently.The effectiveness of the proposed model and solution method for enhancing the distribution system resilience is verified on the modified IEEE 33-bus distribution system and modified realworld zone of Caracas 141-bus distribution system.
基金supported by National Natural Science Foundation of China(No.52377115)。
文摘With the rapid integration of communication and information technology into substations,the risk of cyber attacks has significantly increased.Attackers may infiltrate substation networks,manipulate switches,and disrupt power lines,potentially causing severe damage to the power system.To minimize such risks,this paper proposes a three-layer defender-attacker-defender(DAD)model for optimally allocating limited defensive resources to substations.To model the uncertainty surrounding the knowledge of defender of potential attacks in realworld scenarios,we employ a fuzzy analytic hierarchy process combined with the decision-making trial and evaluation laboratory(FAHP-DEMATEL).This method accounts for the attack resource uncertainty by utilizing intelligence data on factors potentially influenced by attackers,which serves as an evaluation metric to simulate the likelihood of various attack scenarios.These uncertainty probabilities are then incorporated into the substation DAD model consisting three layers of agents:the decision-maker,the attacker,and the operator.The decision-maker devises a defense strategy before the attack,while the attacker aims to identify the strategy that causes the maximum load loss.Meanwhile,the operator seeks to minimize the load loss through optimal power flow scheduling.To solve the model,the original problem is transformed into a two-layer subproblem and a single-layer master problem,which are solved iteratively using a column-and-constraint generation algorithm.Case studies conducted on the IEEE RTS-96 system and the IEEE 118-node system demonstrate the effectiveness and practicality of the proposed model.Comparative experiments further highlight the advantages of the proposed model.
