Regulatory mechanisms for climate-resilient urban energy systems

被引:2
作者
Shi, Jianping [1 ,2 ]
Fan, Hongyi [2 ]
机构
[1] Shanghai Univ Polit Sci & Law, Sch Int Law, Shanghai 201701, Peoples R China
[2] Jiangxi Univ Software Profess Technol, Sch Econ Management, Nanchang 330041, Jiangxi, Peoples R China
关键词
Resilience reconfiguration; Extreme weather condition; Particle swarm optimization; Smart grid; DISTRIBUTION NETWORKS; OPTIMIZATION; ALGORITHM;
D O I
10.1016/j.scs.2024.105215
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Disruptions to customer services are largely caused by weather-related blackouts. As a result, grid operators face a number of problems when operating grids under severe weather circumstances. A smart grid's capability of resiliency and profit can be increased through resilience enhancement programs (REPs) in the present study. This method improves resilience through the simulation of outages caused by weather, which is followed by rescheduling distribution networks and energy storage facilities, shifting loads, and dynamically recalibrating distribution networks as needed. The study examines per-hour variations in weather-dependent error likelihoods. In REPs, sources are rescheduled and appropriate reconfigurations are selected to minimize weather impacts in advance of the occurrence of a fault. It is likewise possible to isolate faulty components following a fault that has been initiated through reconfiguration. From the perspective of the system operator, the objective of the suggested method is to minimize the operating costs of the distribution networks and compensate for expenses associated with unsupplied power, and to maximize the profits of the electricity resource owners. The optimal result from a Pareto optimal set is determined by a multi-objective optimization algorithm utilizing particle swarm optimization (PSO). Measures for assessing resilience have been used for evaluating the effectiveness and impact of the suggested REPs. Simulations have proven that the suggested scheme is more efficient than conventional grids in cases of severe weather.
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收藏
页数:13
相关论文
共 23 条
[1]  
Abdubannaev J., 2020, 2020 IEEE/IAS industrial and commercial power system Asia (I&CPS Asia)
[2]   Key performance indicators for Smart Campus and Microgrid [J].
Alrashed, Saleh .
SUSTAINABLE CITIES AND SOCIETY, 2020, 60
[3]   Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems [J].
Canizes, Bruno ;
Soares, Joao ;
Vale, Zita ;
Khodr, H. M. .
ENERGY, 2012, 45 (01) :1007-1017
[4]   Real-Time Allocation of Multi-Mobile Resources in Integrated Distribution and Transportation Systems for Resilient Electrical Grid [J].
Erenoglu, Ayse Kubra ;
Erdinc, Ozan .
IEEE TRANSACTIONS ON POWER DELIVERY, 2023, 38 (02) :1108-1119
[5]   Urban resilience: A conceptual framework [J].
Gomes Ribeiro, Paulo Jorge ;
Pena Jardim Goncalves, Luis Antonio .
SUSTAINABLE CITIES AND SOCIETY, 2019, 50
[6]   Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience [J].
Hussain, Akhtar ;
Van-Hai Bui ;
Kim, Hak-Man .
APPLIED ENERGY, 2019, 240 :56-72
[7]   Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event [J].
Jufri, Fauzan Hanif ;
Kim, Jun-Sung ;
Jung, Jaesung .
ENERGIES, 2017, 10 (11)
[8]   Automated Distribution Networks Reliability Optimization in the Presence of DG Units Considering Probability Customer Interruption: A Practical Case Study [J].
Karimi, Hassan ;
Niknam, Taher ;
Dehghani, Moslem ;
Ghiasi, Mohammad ;
GhasemiGarpachi, Mina ;
Padmanaban, Sanjeevikumar ;
Tabatabaee, Sajad ;
Aliev, Hamdulah .
IEEE ACCESS, 2021, 9 :98490-98505
[9]   Switches optimal placement of automated distribution networks with probability customer interruption cost model: A case study [J].
Karimi, Hassan ;
Niknam, Taher ;
Aghaei, Jamshid ;
GhasemiGarpachi, Mina ;
Dehghani, Moslem .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 127
[10]  
Khouzam KY, 2008, IEEE POW ENER SOC GE, P191