Elasticity modelling of price-based demand response programs considering customer's different behavioural patterns

被引:8
|
作者
Kansal, Gaurav [1 ]
Tiwari, Rajive [1 ]
机构
[1] Malaviya Natl Inst Technol, Dept Elect Engn, Jaipur 302017, Rajasthan, India
来源
关键词
Demand response; Price elasticity model; Price elasticity of demand; Stochastic elasticity; NONLINEAR MODELS; SYSTEM;
D O I
10.1016/j.segan.2023.101244
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Mathematical modelling of demand response programs (DRPs) aids regulators and policymakers in analysing the advantages of price-elastic loads on distribution system and electricity market. This mathematical model is used to find updated demand after DR for calculation of different technical and economical indices. In accordance with the concept of price elasticity of demand, an economic model of price sensitive load is developed. Price elasticity model (PEM) is a very useful tool to assess customer participation in DRPs. In this work PEM has been attributed on the ground of price elasticity of demand where PEM has been modelled by means of analytical and stochastic elasticity approach. Analytical elasticity has been modelled on the basis of ideal (lossless) approach whereas Stochastic elasticity has been modelled using Ornstein-Uhlenbeck process based on load flexibility and results obtained from these approaches were compared to check the acceptability of DR programs. It is observed that the proposed APEM and SPEM approaches provides maximum peak curtailment of 15% and 10.2% respectively during peak hours. Similarly, it is also noticed that both approaches improve load factor by reducing its peak-to-valley span by 47.33% and 35.7% respectively. The proposed models are investigated on standard IEEE 33-bus distribution system and modified IEEE 33-bus distribution system and are compared with already existing DR models. Technical and economical comparison of proposed approaches on both distribution systems shows that proposed models are competent enough to model customer behaviour properly.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Price-based demand response for household load management with interval uncertainty
    Judge, Malik Ali
    Manzoor, Awais
    Maple, Carsten
    Rodrigues, Joel J. P. C.
    ul Islam, Saif
    ENERGY REPORTS, 2021, 7 : 8493 - 8504
  • [32] Residential electricity pricing in China: The context of price-based demand response
    Yang, Changhui
    Meng, Chen
    Zhou, Kaile
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 81 : 2870 - 2878
  • [33] Price-Based Demand Response Mechanism of Prosumer Groups Considering Real-Time Carbon Emission Reduction
    Zhu Y.
    Qi T.
    Wu X.
    Liu D.
    Hua H.
    Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2023, 57 (04): : 452 - 463
  • [34] Incentive Compatible Pricing for Enhancing the Controllability of Price-Based Demand Response
    Sun, Xiaotian
    Xie, Haipeng
    Xiao, Yunpeng
    Bie, Zhaohong
    IEEE TRANSACTIONS ON SMART GRID, 2024, 15 (01) : 418 - 430
  • [35] Price-Based Demand Response of Energy Storage Resources in Commercial Buildings
    Kim, Young-Jin
    Norford, Leslie K.
    2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,
  • [36] Price-based low-carbon demand response considering the conduction of carbon emission costs in smart grids
    Yang, Chao
    He, Binghao
    Liao, Huanxin
    Ruan, Jiaqi
    Zhao, Junhua
    FRONTIERS IN ENERGY RESEARCH, 2022, 10
  • [37] Tradeoffs in cost competitiveness and emission reduction within microgrid sustainable development considering price-based demand response
    Chen, Yizhong
    Li, Jing
    He, Li
    SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 703
  • [38] A Perspective on Reinforcement Learning in Price-based Demand Response for Smart Grid
    Lu, Renzhi
    Hong, Seung Ho
    Zhang, Xiongfeng
    Ye, Xun
    Song, Won Seok
    PROCEEDINGS 2017 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI), 2017, : 1822 - 1823
  • [39] Estimating impact of price-based demand response in contemporary distribution systems
    Sharma, Bhuvan
    Gupta, Nikhil
    Niazi, K. R.
    Swarnkar, Anil
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2022, 135
  • [40] Optimal Coordination of Price-based Demand Response and Microturbine Dispatch in Microgrids
    Zeng, Kaiwen
    Wang, Haizhu
    Liu, Jianing
    Hu, Chunchao
    Tang, Shengwei
    2020 INTERNATIONAL CONFERENCE ON SMART GRIDS AND ENERGY SYSTEMS (SGES 2020), 2020, : 662 - 666