An Optimal Sizing Method for Hybrid Electrical and Thermal Energy Storage System Considering Wind Power Accommodation

doi:10.12204/j.issn.1000-7229.2020.12.002

Abstract

Abstract:

Large scale wind power integration affects the safe and stable operation of the power system, resulting in the phenomenon of wind abandonment and limiting the development of wind power. Considering the coordinated operation of power system and thermal system, the level of wind power accommodation can be effectively improved by using a hybrid electrical and thermal energy storage system to exchange energy with power grid. This paper proposed an optimal sizing method for hybrid electrical and thermal energy storage system considering wind power accommodation. Firstly, wind power is modeled according to historical wind power data, and target grid-connected wind power meeting the grid-connected requirement is obtained. Then, the hybrid electrical and thermal energy storage system is composed of electric energy storage, electric boiler and heat storage. The optimal sizing model of the hybrid electrical and thermal energy storage system is established considering the operational constraints and taking the minimum total cost of the system as the objective and the economic and optimal sizing results of hybrid electrical and thermal energy storage system are solved. Finally, the proposed method is verified by measured data. The case study results illustrate the effectiveness of the proposed method to optimize the size of the hybrid electrical and thermal energy storage system. Furthermore, the proposed method can improve the wind power accommodation effectively and ensure the overall economic benefits of the system.

Key words: wind power accommodation, optimal sizing, hybrid energy storage system, combined heat and power

CLC Number:

TM73

ZHU Bingquan, QIAN Weiting, ZHANG Jun, WAN Can, CHEN Xinjian, ZHU Yilun. An Optimal Sizing Method for Hybrid Electrical and Thermal Energy Storage System Considering Wind Power Accommodation[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(12): 16-24.

Figures/Tables 10

Fig.1 Structure of the electricity-heat combined systems

Fig.2 Flow chart of Metropolis sampling

Fig.3 Typical daily electric load curves

Fig.4 Typical daily thermal load curves

Fig.5 Curves of typical daily forecast wind power and target grid-connected wind power in summer

Table 1 Parameters of hybrid electrical and thermal energy storage system

Table 2 Optimized results of the size

Fig.6 The SOC of electric energy storage and the stored energy in thermal storage in typical summer day

Fig.7 Power outputs of electric boiler in typical summer day

Fig.8 Curves of forecast wind power and actual grid-connected wind power in typical summer day

References 23

[1]	万灿, 贾妍博, 李彪, 等. 城镇能源互联网能源交易模式和用户响应研究现状与展望[J]. 电力系统自动化, 2019,43(14):29-40.
	WAN Can, JIA Yanbo, LI Biao, et al. Research status and prospect of energy trading mode and user demand response in urban energy Internet[J]. Automation of Electric Power Systems, 2019,43(14):29-40.
[2]	WAN C, XU Z, PINSON P, et al. Probabilistic forecasting of wind power generation using extreme learning machine[J]. IEEE Transactions on Power Systems, 2014,29(3):1033-1044. doi: 10.1109/TPWRS.2013.2287871 URL
[3]	JIANG Y B, WAN C, CHEN C, et al. A hybrid stochastic-interval operation strategy for multi-energy microgrids[J]. IEEE Transactions on Smart Grid, 2020,11(1):440-456. doi: 10.1109/TSG.5165411 URL
[4]	国家能源局. 2019年第一季度风电并网运行情况[EB/OL]. (2019-04-29)[2020-07-03]. http://www.nea.gov.cn/2019-04/29/c_138022113.htm.
[5]	吕泉, 姜浩, 陈天佑, 等. 基于电锅炉的热电厂消纳风电方案及其国民经济评价[J]. 电力系统自动化, 2014,38(1):6-12. doi: 10.7500/AEPS201206124 URL
	LÜ Quan, JIANG Hao, CHEN Tianyou, et al. Wind power accommodation by combined heat and power plant with electric boiler and its national economic evaluation[J]. Automation of Electric Power Systems, 2014,38(1):6-12. doi: 10.7500/AEPS201206124 URL
[6]	任建文, 许英强, 董圣孝. 考虑储能参与的含高比例风电互联电力系统分散式调度模型[J]. 电网技术, 2018,42(4):1079-1085.
	REN Jianwen, XU Yingqiang, DONG Shengxiao. A decentralized scheduling model with energy storage participation for interconnected power system with high wind power penetration[J]. Power System Technology, 2018,42(4):1079-1085.
[7]	MIRANDA I, SILVA N, LEITE H. A holistic approach to the integration of battery energy storage systems in island electric grids with high wind penetration[J]. IEEE Transactions on Sustainable Energy, 2016,7(2):775-785. doi: 10.1109/TSTE.2015.2497003 URL
[8]	ZHAO P, WANG J F, DAI Y P. Capacity allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level[J]. Renewable Energy, 2015,75:541-549. doi: 10.1016/j.renene.2014.10.040 URL
[9]	董凌, 年珩, 范越, 等. 能源互联网背景下共享储能的商业模式探索与实践[J]. 电力建设, 2020,41(4):38-44.
	DONG Ling, NIAN Heng, FAN Yue, et al. Exploration and practice of business model of shared energy storage in energy Internet[J]. Electric Power Construction, 2020,41(4):38-44.
[10]	王振浩, 杨璐, 田春光, 等. 考虑风电消纳的风电-电储能-蓄热式电锅炉联合系统能量优化[J]. 中国电机工程学报, 2017,37(S1):137-143.
	WANG Zhenhao, YANG Lu, TIAN Chunguang, et al. Energy optimization for combined system of wind-electric energy storage-regenerative electric boiler considering wind consumption[J]. Proceedings of the CSEE, 2017,37(S1):137-143.
[11]	李国庆, 庄冠群, 田春光, 等. 基于大规模储能融合蓄热式电锅炉的风电消纳多目标优化控制[J]. 电力自动化设备, 2018,38(10):46-52, 59.
	LI Guoqing, ZHUANG Guanqun, TIAN Chunguang, et al. Multi-objective optimization control of wind power consumption based on regenerative electric boiler system integrated with large-scale energy storage[J]. Electric Power Automation Equipment, 2018,38(10):46-52, 59.
[12]	葛维春, 张艳军, 高超, 等. 基于风电消纳能力态势划分的源荷储系统分阶段优化策略[J]. 电力系统自动化, 2019,43(15):26-33, 70.
	GE Weichun, ZHANG Yanjun, GAO Chao, et al. Phased optimal strategy of source-load-storage system based on state partition of accommodation capacity of wind power[J]. Automation of Electric Power Systems, 2019,43(15):26-33, 70.
[13]	徐飞, 闵勇, 陈磊, 等. 包含大容量储热的电-热联合系统[J]. 中国电机工程学报, 2014,34(29):5063-5072. doi: 10.13334/j.0258-8013.pcsee.2014.29.007 URL
	XU Fei, MIN Yong, CHEN Lei, et al. Combined electricity-heat operation system containing large capacity thermal energy storage[J]. Proceedings of the CSEE, 2014,34(29):5063-5072.
[14]	JIANG Y B, WAN C, BOTTERUD A, et al. Exploiting flexibility of district heating networks in combined heat and power dispatch[J]. IEEE Transactions on Sustainable Energy, 2020,11(4):2174-2188. doi: 10.1109/TSTE.5165391 URL
[15]	WAN C, XU Z, PINSON P, et al. Optimal prediction intervals of wind power generation[J]. IEEE Transactions on Power Systems, 2014,29(3):1166-1174. doi: 10.1109/TPWRS.2013.2288100 URL
[16]	杨楠, 黄禹, 叶迪, 等. 基于NACEMD和改进非参数核密度估计的风功率波动性概率分布研究[J]. 电网技术, 2019,43(3):910-917.
	YANG Nan, HUANG Yu, YE Di, et al. Study on probability distribution of wind power fluctuation based on NACEMD and improved nonparametric kernel density estimation[J]. Power System Technology, 2019,43(3):910-917.
[17]	DAVIS R A, LII K S, POLITIS D N. Remarks on some nonparametric estimates of a density function[M] //Selected Works of Murray Rosenblatt. New York: Springer New York, 2011: 95-100.
[18]	EPANECHNIKOV V A. Non-parametric estimation of a multivariate probability density[J]. Theory of Probability & Its Applications, 1969,14(1):153-158.
[19]	GILKS W R, BEST N G, TAN K K C. Adaptive rejection metropolis sampling within Gibbs sampling[J]. Journal of the Royal Statistical Society: Series C (Applied Statistics), 1995,44(4):455-472.
[20]	全国电力监管标准化技术委员会. 风电场接入电力系统技术规定: GB/T 19963—2011[S]. 北京: 中国标准出版社, 2012.
[21]	崔杨, 陈志, 严干贵, 等. 基于含储热热电联产机组与电锅炉的弃风消纳协调调度模型[J]. 中国电机工程学报, 2016,36(15):4072-4080.
	CUI Yang, CHEN Zhi, YAN Gangui, et al. Coordinated wind power accommodating dispatch model based on electric boiler and CHP with thermal energy storage[J]. Proceedings of the CSEE, 2016,36(15):4072-4080.
[22]	ZHAO C F, WAN C, SONG Y H. An adaptive bilevel programming model for nonparametric prediction intervals of wind power generation[J]. IEEE Transactions on Power Systems, 2020,35(1):424-439. doi: 10.1109/TPWRS.59 URL
[23]	吕泉, 陈天佑, 王海霞, 等. 含储热的电力系统电热综合调度模型[J]. 电力自动化设备, 2014,34(5):79-85.
	LÜ Quan, CHEN Tianyou, WANG Haixia, et al. Combined heat and power dispatch model for power system with heat accumulator[J]. Electric Power Automation Equipment, 2014,34(5):79-85.