Economic Dispatch of Virtual Power Plant Based on New Carbon Emission Model

被引:0
作者
Wang, Pengcheng [1 ]
Ge, Yuan [1 ]
Wang, Yang [2 ]
Lin, Qiyou [2 ]
Chen, Renfeng [3 ]
Wang, Jie [1 ]
机构
[1] Anhui Polytech Univ, Sch Elect Engn, Wuhu, Peoples R China
[2] Wuhu Power Supply Co, State Grid Anhui Elect Power Co, Wuhu, Peoples R China
[3] Anhui Usem Technol Co Ltd, Wuhu, Peoples R China
来源
2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年
基金
中国国家自然科学基金;
关键词
carbon emission modeling; virtual power plant; economic dispatch; crow sine cosine search algorithm; STRATEGY;
D O I
10.1109/CCDC58219.2023.10326591
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In view of the problem that the existing carbon emission models only consider the factor of output, which cannot reflect the real carbon emissions, and considering that both climbing and environmental factors will affect carbon emissions, a new carbon emission model is proposed through Pearson Correlation Coefficient verification, and the effectiveness of the proposed model is verified through Root Mean Square Error and Coefficient of Determination index. Based on the above model, the maximum benefit of virtual power plant is the objective function, and the penalty function method is used to introduce constraints into the objective function, and a virtual power plant economic optimal dispatching model with "wind-photovoltaic-gas-storage" is constructed. Aiming at the problems such as high dimension nonlinearity, strong constraint, and difficulty in solving the model, the crow sine cosine search algorithm is proposed to solve the problem. The feasibility and superiority of the proposed model and solution strategy are verified through simulation, which can effectively improve the adjustment income of the virtual power plant and the consumption ratio of renewable energy.
引用
收藏
页码:4583 / 4588
页数:6
相关论文
共 23 条
  • [1] A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm
    Askarzadeh, Alireza
    [J]. COMPUTERS & STRUCTURES, 2016, 169 : 1 - 12
  • [2] Hannan M, 2019, IEEE ACCESS, V7
  • [3] Hashmi A., 2011, 2011 ACM/IEEE 38th International Symposium on Computer Architecture (ISCA), P1
  • [4] An Auction-Based Local Market Clearing for Energy Management in a Virtual Power Plant
    Heydarian-Forushani, Ehsan
    Ben Elghali, Seifeddine
    Zerrougui, Mohamed
    La Scala, Massimo
    Mestre, Pascal
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2022, 58 (05) : 5724 - 5733
  • [5] HUANG KW, 2019, COMPUTATIONAL INTELL, V12, P426, DOI DOI 10.2991/IJCIS.2018.125905658
  • [6] HUSSIEN AG, 2020, IEEE ACCESS, V8
  • [7] Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS
    Kaya, Heysem
    Tufekci, Pinar
    Uzun, Erdinc
    [J]. TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2019, 27 (06) : 4783 - 4796
  • [8] Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
  • [9] A Robust Distributed Economic Dispatch Strategy of Virtual Power Plant Under Cyber-Attacks
    Li, Peikai
    Liu, Yun
    Xin, Huanhai
    Jiang, Xichen
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (10) : 4343 - 4352
  • [10] Bidding Strategy of Virtual Power Plant for Participating in Energy and Spinning Reserve Markets-Part I: Problem Formulation
    Mashhour, Elaheh
    Moghaddas-Tafreshi, Seyed Masoud
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (02) : 949 - 956