A pool-based electricity retail markets integrating renewable energy sources and electric vehicles in the presence of demand response program and conditional value at risk to enhance energy security

被引:3
|
作者
Kong, Chunhua [1 ]
Wei, Jiatong [1 ]
Zhao, Zihan [2 ]
机构
[1] Jilin Commun Polytech, Dept Automot Engn, Changchun 130012, Peoples R China
[2] Cit Secur Co Ltd, Shanghai Wanyuan Rd Secur Sales Dept, Shanghai 201100, Peoples R China
关键词
Demand-side management; Electric vehicles; Renewable energy sources; Pool-based electricity retail markets; Conditional value at risk method; ISLANDING DETECTION; UNCERTAINTY; STRATEGY;
D O I
10.1016/j.compeleceng.2024.109421
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In restructured power systems, energy security has become a critical concern, driven by changes in laws and regulations and underscored by a defensive approach implemented by the independent system operator. This alignment highlights a strong interdependence between energy security, energy supply, and the economic aspects of energy management. The paper explores how consumers energy supply in restructured systems can be managed through Demand-Side Management (DSM) and Demand Response (DR) programs, considering economic efficiency and risk in scenarios that include Renewable Energy Sources (RES), suitable storage systems, and electric vehicles (EVs). An energy security index is introduced to evaluate the impact of DR programs on both electrical and thermal energy, considering the economic risks involved. A hybrid pool-based electricity retail market approach is utilized to optimize energy security, supply, and consumption. The significant roles of RES, storage systems, and EVs are highlighted in this context. Economic and environmental optimization is achieved using the Conditional Value at Risk (CVaR) method, facilitating strategic decision-making under varied risk conditions. The energy supply security is further analyzed in the presence of electricity market retailers, exploring different pricing strategies. A Mixed-Integer Programming (MIP) model, implemented in GAMS software with the CONOPT solver, is used to examine pricing methods such as Time-of-Use (TOU) and realtime pricing. Findings reveal that DR programs lead to substantial increases in retailer profit and energy supply security value, with real-time pricing showing a significant 23.5 % increase in energy supply security value and a 24.5 % increase in retailer profit compared to fixed tariff pricing.
引用
收藏
页数:21
相关论文
共 15 条
  • [1] Reviewing Demand Response for Energy Management with Consideration of Renewable Energy Sources and Electric Vehicles
    Chatuanramtharnghaka, Benjamin
    Deb, Subhasish
    Singh, Ksh Robert
    Ustun, Taha Selim
    Kalam, Akhtar
    WORLD ELECTRIC VEHICLE JOURNAL, 2024, 15 (09):
  • [2] Stochastic optimal pricing for retail electricity considering demand response, renewable energy sources and environmental effects
    Neishaboori, Morteza
    Arshadi Khamseh, Alireza
    Mirzazadeh, Abolfazl
    Esmaeeli, Mostafa
    Davari Ardakani, Hamed
    JOURNAL OF REVENUE AND PRICING MANAGEMENT, 2024, 23 (05) : 435 - 451
  • [3] Retailer energy management of electric energy by combining demand response and hydrogen storage systems, renewable sources and electric vehicles
    Karami, Mohammad
    Zadehbagheri, Mahmoud
    Kiani, Mohammad Javad
    Nejatian, Samad
    INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2023, 48 (49) : 18775 - 18794
  • [4] Smart home energy management using demand response with uncertainty analysis of electric vehicle in the presence of renewable energy sources
    Kanakadhurga, Dharmaraj
    Prabaharan, Natarajan
    APPLIED ENERGY, 2024, 364
  • [5] A sustainable framework for long-term planning of the smart energy hub in the presence of renewable energy sources, energy storage systems and demand response program
    Honarmand, Hamed Asgarian
    Rashid, Sara Mahmoudi
    JOURNAL OF ENERGY STORAGE, 2022, 52
  • [6] Optimal scheduling of plug-in electric vehicles and renewable micro-grid in energy and reserve markets considering demand response program
    Aliasghari, Parinaz
    Mohammadi-Ivatloo, Behnam
    Alipour, Manijeh
    Abapour, Mehdi
    Zare, Kazem
    JOURNAL OF CLEANER PRODUCTION, 2018, 186 : 293 - 303
  • [7] A hierarchical optimization approach to maximize hosting capacity for electric vehicles and renewable energy sources through demand response and transmission expansion planning
    Almutairi, Sulaiman Z.
    Alharbi, Abdullah M.
    Ali, Ziad M.
    Refaat, Mohamed M.
    Aleem, Shady H. E. Abdel
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [9] Customer directrix load-based large-scale demand response for integrating renewable energy sources
    Fan, Shuai
    Li, Zuyi
    Yang, Lin
    He, Guangyu
    ELECTRIC POWER SYSTEMS RESEARCH, 2020, 181
  • [10] Economic management and planning based on a probabilistic model in a multi-energy market in the presence of renewable energy sources with a demand-side management program
    Bodong, Song
    Wiseong, Jin
    Chengmeng, Li
    Khakichi, Aroos
    ENERGY, 2023, 269