Pricing Method for Season of Use in Integrated Energy Park

doi:10.12096/j.2096-4528.pgt.21119

Abstract

Abstract:

Integrated energy park is the basic unit of new electric power system dominated by renewable energy. Depending on distributed generators, the energy production and consumption nearby and self-balance of park are achieved. The contradiction of seasonal load mismatch between distributed generators and users can be released by tapping demand response potential and stipulating different season of use (SOU) price. A pricing method for SOU price in integrated energy park was put forward accordingly. First of all, considering characteristics of load and demand response, users were classified by k-means clustering algorithm. Then, according to unbalance load of park, SOU periods were determined by k-means clustering algorithm. At last, the optimization model was established to stipulate SOU price of different types of users. As the case shown, based on this method, SOU price can promote local consumption of distributed generators efficiently and raise the utilization ratio of clean energy and overall economic benefit of park.

Key words: new power system, integrated energy park, distributed generator, season of use price, k-means clustering, demand response

CLC Number:

TK 01

Jiangwu DU, Xiaoqiang TANG, Zhiwei LUO, Dunnan LIU, Jixu CHEN, Erfeng XU, Sheng BI. Pricing Method for Season of Use in Integrated Energy Park[J]. Power Generation Technology, 2023, 44(2): 261-269.

Figures/Tables 9

Fig. 1 Monthly load of distributed generators and users

Fig. 2 Flow of user classification based on k-means clustering algorithm

Fig. 3 Load of distributed generators and users, and the unbalance load of park

Tab. 1 CH index with different number of user types

用户分类数量	2	3	4	5
CH指标值	255.8	237 705.1	181 753.1	159 034.7

Fig. 4 Monthly load of three types of users

Fig. 5 Price elasticity matrix of three types of users

Tab. 2 SOU periods and SOU price of different types of users

时段	月份	1类用户	2类用户	3类用户
枯	3—5月	0.506 9	0.613 3	0.557 6
平	2月、6—10月	0.557 6	0.674 7	0.613 3
丰	1月、11—12月	0.613 3	0.742 1	0.674 7

Fig. 6 Unbalance load of park before and after stipulating season of use price

Tab. 3 Changes before and after stipulating season of use price

指标	执行丰枯电价前	执行丰枯电价后	执行前后变化
供需不匹配度/%	9.6	5.8	-3.8
园区综合电价/[元/(kW∙h)]	0.65	0.61	-0.04

References 28

1	新华社．习近平在气候雄心峰会上的讲话(全文)[EB/OL]．(2020-12-13)[2021-10-15]．． doi:10.1007/978-1-4614-0539-9_727
	Xinhua News Agency ．Full text：President Xi's speech at climate ambition summit[EB/OL]．(2020-12-13)[2021-10-15]．． doi:10.1007/978-1-4614-0539-9_727
2	新华社．习近平主持召开中央财经委员会第九次会议[EB/OL]．(2021-03-15)[2021-10-15]．． doi:10.1055/s-0041-1731212
	Xinhua News Agency ．A meeting of the central committee for financial and economic affairs presided over by President Xi[EB/OL]．(2021-03-15)[2021-10-15]．． doi:10.1055/s-0041-1731212
3	曾鸣，杨雍琦，刘敦楠，等．能源互联网“源-网-荷-储”协调优化运营模式及关键技术[J]．电网技术，2016，40(1)：114-124． doi:10.16081/j.issn.1006-6047.2016.02.017
	ZENG M， YANG Y Q， LIU D N，et al ．“Generation-grid-load-storage”coordinative optimal operation mode of energy internet and key technologies[J]．Power System Technology，2016，40(1)：114-124． doi:10.16081/j.issn.1006-6047.2016.02.017
4	李政洁，撖奥洋，周生奇，等．计及综合需求响应的综合能源系统优化调度[J]．电力系统保护与控制，2021，49(21)：36-42． doi:10.19635/j.cnki.csu-epsa.000740
	LI Z J， HAN A Y， ZHOU S Q，et al ．Optimization of an integrated energy system considerring integrated demand response[J]．Power System Protection and Control，2021，49(21)：36-42． doi:10.19635/j.cnki.csu-epsa.000740
5	刘敦楠，唐天琦，杨建华，等．面向能源互联网的微平衡调度交易设计[J]．电力系统自动化，2017，41(10)：1-8． doi:10.7500/AEPS20160728017
	LIU D N， TANG T Q， YANG J H，et al ．Energy internet based micro balance dispatching and trading design[J]．Automation of Electric Power Systems，2017，41(10)：1-8． doi:10.7500/AEPS20160728017
6	刘敦楠，徐尔丰，许小峰．面向园区微网的“源-网-荷-储”一体化运营模式[J]．电网技术，2018，42(3)：681-689．
	LIU D N， XU E F， XU X F ．“Source-network-load-storage” integrated operation model for microgrid in park[J]．Power System Technology，2018，42(3)：681-689．
7	戚艳，刘敦楠，徐尔丰，等．面向园区能源互联网的综合能源服务关键问题及展望[J]．电力建设，2019，40(1)：123-132． doi:10.3969/j.issn.1000-7229.2019.01.015
	QI Y， LIU D N， XU E F，et al ．Key issues and prospects of integrated energy service for Energy Internet in park[J]．Electric Power Construction，2019，40(1)：123-132． doi:10.3969/j.issn.1000-7229.2019.01.015
8	杨洪朝，杨迪，孟科．高比例可再生能源渗透下多虚拟电厂多时间尺度协调优化调度[J]．智慧电力，2021，49(2)：60-68． doi:10.3969/j.issn.1673-7598.2021.02.011
	YANG H C， YANG D， MENG K ．Multi-time scale coordination optimal scheduling of multiple virtual power plants with high-penetration renewable energy integration[J]．Smart Power，2021，49(2)：60-68． doi:10.3969/j.issn.1673-7598.2021.02.011
9	姜海洋，杜尔顺，朱桂萍，等．面向高比例可再生能源电力系统的季节性储能综述与展望[J]．电力系统自动化，2020，44(19)：194-207． doi:10.7500/AEPS20200204003
	JIANG H Y， DU E S， ZHU G P，et al ．Review and prospect of seasonal energy storage for power system with high proportion of renewable energy[J]．Automation of Electric Power Systems，2020，44(19)：194-207． doi:10.7500/AEPS20200204003
10	束洪春，董俊，吴水军，等．销售侧分行业实行丰枯峰谷分时电价初探[J]．电力系统自动化，2006，30(14)：36-40． doi:10.3321/j.issn:1000-1026.2006.14.008
	SHU H C， DONG J， WU S J，et al ．A preliminary discussion on implementing of peak-valley and time-of-use and season-of-use price for different industries at demand side[J]．Automation of Electric Power Systems，2006，30(14)：36-40． doi:10.3321/j.issn:1000-1026.2006.14.008
11	雷霞，刘俊勇．丰枯-峰谷电价中用户反应度模型研究[J]．电力需求侧管理，2007，9(2)：11-13． doi:10.3969/j.issn.1009-1831.2007.02.003
	LEI X， LIU J Y ．Research on customer response indicator model in abundant-dry water & peak-valley price[J]．Power DSM，2007，9(2)：11-13． doi:10.3969/j.issn.1009-1831.2007.02.003
12	张钦，王锡凡，王建学，等．丰枯季节电价决策模型分析[J]．电力系统自动化，2007，31(24)：7-11． doi:10.3321/j.issn:1000-1026.2007.24.002
	ZHANG Q， WANG X F， WANG J X，et al ．Decision model analysis of season-of-use price[J]．Automation of Electric Power Systems，2007，31(24)：7-11． doi:10.3321/j.issn:1000-1026.2007.24.002
13	雷霞，刘俊勇，党晓强．对电力大用户定价模式的研究[J]．电力系统及其自动化学报，2010，22(3)：60-66． doi:10.3969/j.issn.1003-8930.2010.03.011
	LEI X， LIU J Y， DANG X Q ．Research on pricing mode of large consumers in electricity supply system[J]．Proceedings of the CSU-EPSA，2010，22(3)：60-66． doi:10.3969/j.issn.1003-8930.2010.03.011
14	王羽．风电出力时序特性及其对省级电网的影响[J]．发电技术，2018，39(5)：475-482． doi:10.12096/j.2096-4528.pgt.2018.074
	WANG Y ．Analysis on the characteristics of wind power time series and its impact on provincial power grid[J]．Power Generation Technology，2018，39(5)：475-482． doi:10.12096/j.2096-4528.pgt.2018.074
15	BUTTLER A， DINKEL F， FRANZ S，et al ．Variability of wind and solar power：an assessment of the current situation in the European Union based on the year 2014[J]．Energy，2016，106：147-161． doi:10.1016/j.energy.2016.03.041
16	姜文玲，王勃，汪宁渤，等．多时空尺度下大型风电基地出力特性研究[J]．电网技术，2017，41(2)：493-499．
	JIANG W L， WANG B， WANG N B，et al ．Research on power output characteristics of large-scale wind power base in multiple temporal and spatial scales[J]．Power System Technology，2017，41(2)：493-499．
17	张宁，周天睿，段长刚，等．大规模风电场接入对电力系统调峰的影响[J]．电网技术，2010，34(1)：152-158． doi:doi:10.1097/ICO.0b013e3182000add
	ZHANG N， ZHOU T R， DUAN C G，et al ．Impact of large-scale wind farm connecting with power grid on peak load regulation demand[J]．Power System Technology，2010，34(1)：152-158． doi:doi:10.1097/ICO.0b013e3182000add
18	张曦，康重庆，张宁，等．太阳能光伏发电的中长期随机特性分析[J]．电力系统自动化，2014，38(6)：6-13． doi:10.7500/AEPS20131009012
	ZHANG X， KANG C Q， ZHANG N，et al ．Analysis of mid/long term random characteristics of photovoltaic power generation[J]．Automation of Electric Power Systems，2014，38(6)：6-13． doi:10.7500/AEPS20131009012
19	时珉，周海，韩雨彤，等．一种考虑季节特性的光伏电站多模型功率预测方法[J]．电网与清洁能源，2019，35(7)：75-82． doi:10.3969/j.issn.1674-3814.2019.07.010
	SHI M， ZHOU H， HAN Y T，et al ．A multi-model power forecasting approach of photovoltaic plant based on seasonal characteristics[J]．Power System and Clean Energy，2019，35(7)：75-82． doi:10.3969/j.issn.1674-3814.2019.07.010
20	张家安，王琨玥，陈建，等．基于空间相关性的分布式光伏出力预测[J]．电力建设，2020，41(3)：47-53．
	ZHANG J A， WANG K Y， CHEN J，et al ．Research on prediction of distributed photovoltaic output considering spatial relevance[J]．Electric Power Construction，2020，41(3)：47-53．
21	路轶，胡晓静，孙毅，等．适应高水电占比的电力现货市场机制设计与实践[J]．电力系统自动化，2021，45(9)：162-170．
	LU Y， HU X J， SUN Y，et al ．Design and practice of electricity spot market mechanism adapting to characteristics of high proportional hydropower[J]．Automation of Electric Power Systems，2021，45(9)：162-170．
22	张童彦，唐飞，廖清芬，等.考虑水电外送及负荷中心功能属性的区域电网规划方法[J]．发电技术，2021，42(6)：741-750． doi:10.12096/j.2096-4528.pgt.20119
	ZHANG T Y， TANG F， LIAN Q F，et al ．Regional power grid planning method considering hydropower transmission and load center function properties[J]．Power Generation Technology，2021，42(6)：741-750． doi:10.12096/j.2096-4528.pgt.20119
23	刘敦楠，徐尔丰，刘明光，等．面向分布式电源就地消纳的园区分时电价定价方法[J]．电力系统自动化，2020，44(20)：19-28． doi:10.7500/AEPS20200123004
	LIU D N， XU E F， LIU M G，et al ．TOU pricing method for park considering local consumption of distributed generator[J]．Automation of Electric Power Systems，2020，44(20)：19-28． doi:10.7500/AEPS20200123004
24	杨甲甲，赵俊华，文福拴，等．电力零售核心业务架构与购售电决策[J]．电力系统自动化，2017，41(14)：10-23． doi:10.7500/AEPS20170220014
	YANG J J， ZHAO J H， WEN F S，et al ．Key business framework and purchase/sale decision-making for electricity retailers[J]．Automation of Electric Power Systems，2017，41(14)：10-23． doi:10.7500/AEPS20170220014
25	宋学伟，刘玉瑶．基于改进k-means聚类的风光发电场景划分[J]．发电技术，2020，41(6)：625-630． doi:10.12096/j.2096-4528.pgt.19090
	SONG X W， LIU Y Y ．Wind and photovoltaic generation scene division based on improved k-means clustering[J]．Power Generation Technology，2020，41(6)：625-630． doi:10.12096/j.2096-4528.pgt.19090
26	陈烨，吴浩，史俊祎，等．奇异值分解方法在日负荷曲线降维聚类分析中的应用[J]．电力系统自动化，2018，42(3)：105-111． doi:10.7500/AEPS20170309008
	CHEN Y， WU H， SHI J Y，et al ．Application of singular value decomposition algorithm to dimension-reduced clustering analysis of daily load profiles[J]．Automation of Electric Power Systems，2018，42(3)：105-111． doi:10.7500/AEPS20170309008
27	刘明明，崔春风，童小娇，等．混合整数非线性规划的算法软件及最新进展[J]．中国科学(数学)，2016，46(1)：1-20． doi:10.1360/N012014-00278
	LIU M M， CUI C F， TONG X J，et al ．Algorithms，softwares and recent developments of mixed integer nonlinear programming[J]．Science in China (Series A)，2016，46(1)：1-20． doi:10.1360/N012014-00278
28	秦祯芳，岳顺民，余贻鑫，等．零售端电力市场中的电量电价弹性矩阵[J]．电力系统自动化，2004，28(5)：16-19． doi:10.3321/j.issn:1000-1026.2004.05.004
	QIN Z F， YUE S M， YU Y X，et al ．Price elasticity matrix of demand in current retail power market[J]．Automation of Electric Power Systems，2004，28(5)：16-19． doi:10.3321/j.issn:1000-1026.2004.05.004

[1]	Jie YANG, Zhe SUN, Xinyi SU, Gang LU, Bo YUAN. A Wireless Multi-Objective Power Sharing Method for Energy Storage System in DC Micro-Grid Considering Oscillatory-Type Power [J]. Power Generation Technology, 2024, 45(2): 341-352.
[2]	Xiaobiao FU, Jiaqi HOU, Baoju LI, Yakun WEN, Xiaowen LAI, Lei GUO, Zhiwei WANG, Yao WANG, Haifeng ZHANG, Dexin LI. A Two-Modal Weather Classification Method and Its Application in Photovoltaic Power Probability Prediction [J]. Power Generation Technology, 2024, 45(2): 299-311.
[3]	Fangfang WANG, Pengwei YANG, Guangjin ZHAO, Qi LI, Xiaona LIU, Shuangchen MA. Development and Challenge of Flexible Operation Technology of Thermal Power Units Under New Power System [J]. Power Generation Technology, 2024, 45(2): 189-198.
[4]	Xingyuan XU, Haoyong CHEN, Yuxiang HUANG, Xiaobin WU, Yushen WANG, Junhao LIAN, Jianbin ZHANG. Challenges, Strategies and Key Technologies for Virtual Power Plants in Market Trading [J]. Power Generation Technology, 2023, 44(6): 745-757.
[5]	Haoyong CHEN, Yuxiang HUANG, Yang ZHANG, Fei WANG, Liang ZHOU, Junbo TANG, Xiaobin WU. Architecture Design of Virtual Power Plant Based on “Three Flow Separation-Convergence” [J]. Power Generation Technology, 2023, 44(5): 616-624.
[6]	Xiyong YANG, Yangfei ZHANG, Gang LIN, Yuzhuo ZHANG, Yunzhan AN, Haotian YANG. Multi-Time Scale Collaborative Optimal Scheduling Strategy for Source-Load-Storage Considering Demand Response [J]. Power Generation Technology, 2023, 44(2): 253-260.
[7]	Chen DONG, Qiang WU, He HUANG, Rui ZHANG, Xiuyuan YANG. Power Grid Topology Identification Based on Immune Algorithm [J]. Power Generation Technology, 2023, 44(1): 125-135.
[8]	Xin YIN, Feng ZHANG, Balati ADILI, Xiqiang CHANG, Wuhui CHEN, Changjun LI, Xueming LI, Shaowei YUAN. Study on Participation of Electricity-driven Thermal Load in Real-time Scheduling of New Power System [J]. Power Generation Technology, 2023, 44(1): 115-124.
[9]	Qian GAO, Junyi YANG, Yu HONG, Xiaolei SUN, Qianjin ZHU, Tian YU, Xin WANG, Linyuan WANG, Zesen LI. Research on Digital Transformation Architecture and Path of Power Grid Development Planning Business Under New Power System Blueprint [J]. Power Generation Technology, 2022, 43(6): 851-859.
[10]	Jianlin LI, Ziyang DING, Haitao LIU, Hang YANG. Research on Grid-Forming Energy Storage Converters and Control Strategies [J]. Power Generation Technology, 2022, 43(5): 679-686.
[11]	Bowen ZHOU, Chao XI, Guangdi LI, Bo YANG. Metaverse Application in Power Systems [J]. Power Generation Technology, 2022, 43(1): 1-9.
[12]	Yan WANG, Xiuyuan YANG, Jianfeng XU, Siqi BU, Zhiqiang XU. Control Strategy of Civil Controllable Load Participating in Demand Response [J]. Power Generation Technology, 2020, 41(6): 638-649.
[13]	Weidong LI,Hongpeng HE. Source-load Cooperative Optimization Dispatch Strategy Considering Wind Power Accommodation [J]. Power Generation Technology, 2020, 41(2): 126-130.
[14]	Jing DING,Xin WANG,Shuwen ZHENG,Yu CHEN,Shiqi SUN. The Impact of DG Access on Microgrid Current Protection [J]. Power Generation Technology, 2019, 40(1): 22-27.
[15]	Guodong ZHANG,Kai LIU. Analysis of Microgrid Energy Management Under the Background of Energy Internet [J]. Power Generation Technology, 2019, 40(1): 17-21.