基于改进模型预测控制的电-气系统新能源功率波动平滑策略

doi:10.12204/j.issn.1000-7229.2021.09.007

电力建设 ›› 2021, Vol. 42 ›› Issue (9): 65-73.doi: 10.12204/j.issn.1000-7229.2021.09.007

• 高比例新能源交直流电网特性分析与运行控制·栏目主持辛业春教授、姜涛教授、吴学光教授、宋晓博士· • 上一篇下一篇

基于改进模型预测控制的电-气系统新能源功率波动平滑策略

余洋¹^,², 贾浩², 陈启维², 范亚洲², 米增强¹^,², 袁玉宝³, 常生强³

1.新能源电力系统国家重点实验室(华北电力大学(保定)),河北省保定市 071003
2.河北省分布式储能与微网重点实验室(华北电力大学(保定)),河北省保定市 071003
3.石家庄科林电气股份有限公司,石家庄市 050222

收稿日期:2020-12-31 出版日期:2021-09-01 发布日期:2021-09-02
通讯作者: 余洋
作者简介:贾浩(1996),男,硕士研究生,主要研究方向为柔性负荷建模与调度等|陈启维(1997),男,硕士研究生,主要研究方向为电力储能技术等|范亚洲(1993),男,硕士研究生,主要研究方向为柔性负荷建模与调度等|米增强(1960),男,教授,博士生导师,主要研究方向为新能源电力系统并网与控制|袁玉宝(1984),男,学士,高级工程师,主要研究方向为电力系统及其自动化|常生强(1978),男,学士,高级工程师,主要研究方向为电力系统及其自动化。
基金资助:
国家重点研发计划资助(2018YFE0122200);中央高校基本科研业务费专项资金资助(2020MS090);河北省智能电网配用电技术创新中心开放课题(20200803)

Fluctuation Smoothing Strategy of New Energy Power for Electricity-Gas Interconnected System Based on Improved Model Predictive Control

YU Yang¹^,², JIA Hao², CHEN Qiwei², FAN Yazhou², MI Zengqiang¹^,², YUAN Yubao³, CHANG Shengqiang³

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, Hebei Province, China
2. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province(North China Electric Power University), Baoding 071003, Hebei Province, China
3. KE Electric Co., Ltd., Shijiangzhuang 050222, China

Received:2020-12-31 Online:2021-09-01 Published:2021-09-02
Contact: YU Yang
Supported by:
National Key Research and Development Program of China(2018YFE0122200)

摘要/Abstract

摘要：

针对新能源功率波动问题,制定了聚合温控负荷与微型燃气轮机共同抑制电-气互联系统联络线功率波动的调控策略。首先,将波动功率进行经验模态分解,然后在建立聚合温控负荷双线性模型与微型燃气轮机数学模型的基础上,提出了基于Lyapunov函数的改进模型预测控制方法,采用改进模型预测控制分别设计了聚合温控负荷与微型燃气轮机的控制律,用于平抑波动功率的高频分量与低频分量。算例仿真表明:在满足聚合温控负荷温度舒适度约束,保持微型燃气轮机预设工作状态的条件下,提出的控制方法能够使它们的输出功率有效跟踪波动功率高频和低频分量;算法兼顾了用户舒适度与调节范围,达到了良好的联络线功率平滑效果。

关键词: 新能源功率波动, 聚合温控负荷(ATCL), 微型燃气轮机, 电-气互联系统, 改进模型预测控制

Abstract:

Aiming at the problem of power fluctuations of new energy sources, a regulation strategy is developed in this paper to suppress the power fluctuations of the tie-line power in an electricity-gas interconnected system with aggregated thermostatically controlled loads (ATCLs) and a micro-turbine. Firstly, the fluctuating power is decomposed by empirical mode decomposition, and then on the basis of the establishment of the ATCLs bilinear model and the mathematical model of the micro-turbine, an improved model predictive control method based on the Lyapunov function is proposed. The control law of the ATCLs and the micro-turbine is designed. The ATCLs and the micro-turbine are aggregated to suppress the high frequency and low frequency components of fluctuating power. The simulation results indicate that the proposed control method can make their output power effectively track the high frequency and low frequency components of fluctuating power under the condition that the temperature comfort constraint of the ATCLs is satisfied and the preset working state of the micro-turbine is maintained. It achieves a good smoothing effect of tie-line power under the condition that user comfort and adjustment range are considered.

Key words: power fluctuation of new energy, aggregated thermostatically controlled load (ATCL), micro-turbine, electricity-gas interconnection system, improved model predictive control

中图分类号:

TM732

余洋, 贾浩, 陈启维, 范亚洲, 米增强, 袁玉宝, 常生强. 基于改进模型预测控制的电-气系统新能源功率波动平滑策略[J]. 电力建设, 2021, 42(9): 65-73.

YU Yang, JIA Hao, CHEN Qiwei, FAN Yazhou, MI Zengqiang, YUAN Yubao, CHANG Shengqiang. Fluctuation Smoothing Strategy of New Energy Power for Electricity-Gas Interconnected System Based on Improved Model Predictive Control[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(9): 65-73.

图/表 9

图1 电-气互联系统结构

Fig.1 Electricity-gas interconnection system structure

图2 本研究整体结构

Fig.2 Overall structure of the study

表1 MT模型参数

Table 1 Model parameters of the MT

图3 光伏、风电及不可控负荷曲线

Fig.3 Curves of PV, wind power and uncontrollable load

图4 ATCLs状态量曲线

Fig.4 Changing curves of state variable for ATCLs

图5 MT状态量曲线

Fig.5 Changing curves of state variable for MT

图6 原始联络线功率波动曲线

Fig.6 Original tie-line power curve

图7 温度设定值变化曲线

Fig.7 Changing curve of temperature setting value for ATCLs

图8 联络线功率控制效果

Fig.8 Tie-line power control performance

参考文献 22

[1]	贾学翠, 李相俊, 万君, 等. 平抑电网大功率扰动的规模化电池储能系统控制方法[J]. 电力建设, 2020, 41(6):69-76.
	JIA Xuecui, LI Xiangjun, WAN Jun, et al. Control method of large-scale battery energy storage system for suppressing the disturbance of power grid[J]. Electric Power Construction, 2020, 41(6):69-76.
[2]	施金晓, 黄文焘, 邰能灵, 等. 电-热联合微网中分布式可再生能源功率波动平抑策略[J]. 中国电机工程学报, 2018, 38(2):537-546, 684.
	SHI Jinxiao, HUANG Wentao, TAI Nengling, et al. A strategy to suppress fluctuation of distributed renewable energy in microgrids with combined heat and power system[J]. Proceedings of the CSEE, 2018, 38(2):537-546, 684.
[3]	WANG D, GE S Y, JIA H J, et al. A demand response and battery storage coordination algorithm for providing microgrid Tie-line smoothing services[J]. IEEE Transactions on Sustainable Energy, 2014, 5(2):476-486. doi: 10.1109/TSTE.2013.2293772 URL
[4]	施金晓, 黄文焘, 邰能灵, 等. 计及群控电热泵的微网联络线功率平滑策略[J]. 电力自动化设备, 2017, 37(6):201-208.
	SHI Jinxiao, HUANG Wentao, TAI Nengling, et al. Microgrid tie-line power smoothing strategy considering group control of electric heat pumps[J]. Electric Power Automation Equipment, 2017, 37(6):201-208.
[5]	沈乃君, 高杰, 何新. 一种基于混合储能系统的风光功率平滑控制策略研究[J]. 电器与能效管理技术, 2019(1):62-68.
	SHEN Naijun, GAO Jie, HE Xin. Research on energy storage control strategy of wind solar storage combined generation system based on power smoothing[J]. Electrical & Energy Management Technology, 2019(1):62-68.
[6]	阚志忠, 柴秀慧, 靳本豪, 等. 基于蓄电池-超级电容混合储能的风力发电功率平滑控制[J]. 燕山大学学报, 2018, 42(6):501-509.
	KAN Zhizhong, CHAI Xiuhui, JIN Benhao, et al. Wind power smoothing control based on battery and super capacitor hybrid energy storage system[J]. Journal of Yanshan University, 2018, 42(6):501-509.
[7]	杨艳红, 裴玮, 邓卫, 等. 计及蓄电池储能寿命影响的微电网日前调度优化[J]. 电工技术学报, 2015, 30(22):172-180.
	YANG Yanhong, PEI Wei, DENG Wei, et al. Day-ahead scheduling optimization for microgrid with battery life model[J]. Transactions of China Electrotechnical Society, 2015, 30(22):172-180.
[8]	王成山, 刘梦璇, 陆宁. 采用居民温控负荷控制的微网联络线功率波动平滑方法[J]. 中国电机工程学报, 2012, 32(25):36-43.
	WANG Chengshan, LIU Mengxuan, LU Ning. A tie-line power smoothing method for microgrid using residential thermostatically-controlled loads[J]. Proceedings of the CSEE, 2012, 32(25):36-43.
[9]	BASHASH S, FATHY H K. Modeling and control of aggregate air conditioning loads for robust renewable power management[J]. IEEE Transactions on Control Systems Technology, 2013, 21(4):1318-1327. doi: 10.1109/TCST.2012.2204261 URL
[10]	余洋, 卢健斌, 谢仁杰, 等. 基于反推控制的聚合温控负荷与发电机励磁协调控制[J]. 电力系统自动化, 2019, 43(16):101-108, 124.
	YU Yang, LU Jianbin, XIE Renjie, et al. Backstepping control based coordinated control of aggregated thermostatically controlled load and generator excitation[J]. Automation of Electric Power Systems, 2019, 43(16):101-108, 124.
[11]	席裕庚, 李德伟, 林姝. 模型预测控制: 现状与挑战[J]. 自动化学报, 2013, 39(3):222-236.
	XI Yugeng, LI Dewei, LIN Shu. Model predictive control-status and challenges[J]. Acta Automatica Sinica, 2013, 39(3):222-236.
[12]	BORHAN H, VAHIDI A, PHILLIPS A M, et al. MPC-based energy management of a power-split hybrid electric vehicle[J]. IEEE Transactions on Control Systems Technology, 2012, 20(3):593-603. doi: 10.1109/TCST.2011.2134852 URL
[13]	LIU M X, SHI Y. Model predictive control of aggregated heterogeneous second-order thermostatically controlled loads for ancillary services[J]. IEEE Transactions on Power Systems, 2016, 31(3):1963-1971. doi: 10.1109/TPWRS.2015.2457428 URL
[14]	王成山, 于波, 肖峻, 等. 平滑微电网联络线功率波动的储能系统容量优化方法[J]. 电力系统自动化, 2013, 37(3):12-17.
	WANG Chengshan, YU Bo, XIAO Jun, et al. An energy storage system capacity optimization method for microgrid Tie-line power flow stabilization[J]. Automation of Electric Power Systems, 2013, 37(3):12-17.
[15]	顾博川, 尤毅, 孙毅, 等. 计及虚拟储能的社区微网联络线功率平滑方法[J]. 广东电力, 2019, 32(5):13-21.
	GU Bochuan, YOU Yi, SUN Yi, et al. A method for smoothing Tie-line power of community microgrid considering virtual energy storage[J]. Guangdong Electric Power, 2019, 32(5):13-21.
[16]	王印松, 曲晓荷, 邓天白, 等. 基于反步法的燃气轮机功率控制器设计[J]. 热力发电, 2016, 45(7):67-71.
	WANG Yinsong, QU Xiaohe, DENG Tianbai, et al. Design of gas-turbine controller based on backstepping method[J]. Thermal Power Generation, 2016, 45(7):67-71.
[17]	ZHANG H S, SU M, WENG S L. Hardware-in-the-loop simulation study on the fuel control strategy of a gas turbine engine[J]. Journal of Engineering for Gas Turbines and Power, 2005, 127(3):693-695. doi: 10.1115/1.1805012 URL
[18]	PARVEZ M, MEKHILEF S, TAN N M L, et al. A robust modified model predictive control (MMPC) based on Lyapunov function for three-phase active-front-end (AFE) rectifier[C]// 2016 IEEE Applied Power Electronics Conference and Exposition (APEC). Long Beach, CA, USA:IEEE, 2016: 1163-1168.
[19]	蔡博戎, 袁越. 一种空调负荷和储能电池的协调控制策略[J]. 电力需求侧管理, 2017, 19(2):4-8.
	CAI Borong, YUAN Yue. A coordinated control strategy of air-conditioning load and energy storage battery[J]. Power Demand Side Management, 2017, 19(2):4-8.
[20]	FANTI M P, MANGINI A M, ROCCOTELLI M, et al. A district energy management based on thermal comfort satisfaction and real-time power balancing[J]. IEEE Transactions on Automation Science and Engineering, 2015, 12(4):1271-1284. doi: 10.1109/TASE.2015.2472956 URL
[21]	谷俊杰, 张永涛, 曹喜果. 一种新的燃气轮机模型建立与其参数求取[J]. 汽轮机技术, 2014, 56(2):123-127, 136.
	GU Junjie, ZHANG Yongtao, CAO Xiguo. A novel model of gas turbine and the extracting of the parameters[J]. Turbine Technology, 2014, 56(2):123-127, 136.
[22]	张兆宇, 刘尚明. 基于数据的燃气轮机建模与控制技术概述[J]. 热力透平, 2019, 48(2):89-95.
	ZHANG Zhaoyu, LIU Shangming. A review of gas turbine modeling and control technology based on operational data[J]. Thermal Turbine, 2019, 48(2):89-95.

基于改进模型预测控制的电-气系统新能源功率波动平滑策略

Fluctuation Smoothing Strategy of New Energy Power for Electricity-Gas Interconnected System Based on Improved Model Predictive Control

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 22

相关文章 4

编辑推荐

Metrics

本文评价

[1]	许志恒，张勇军，余兆荣，王玕. 考虑激励型需求侧响应的电-气互联系统两阶段随机优化调度[J]. 电力建设, 2020, 41(4): 81-89.
[2]	刘凤全, 王成福, 王瑞琪, 杨明, 郭光华, 张健, 杜萍静. 含HVDC与P2G的跨区域电-气互联系统优化调度[J]. 电力建设, 2020, 41(12): 57-67.
[3]	魏震波, 魏平桉, 郭毅, 黄宇涵, 卢炳文. 考虑跨区能流交互计划的多区域电-气综合能源系统分散调度方法[J]. 电力建设, 2020, 41(12): 68-81.
[4]	谈竹奎，瞿凯平，刘斌，王德志，余涛. 含电转气的电-气互联系统多目标优化调度[J]. 电力建设, 2018, 39(11): 51-59.