计及多种柔性负荷的虚拟电厂热电联合鲁棒优化调度模型

doi:10.12204/j.issn.1000-7229.2021.07.001

摘要/Abstract

摘要：

针对热/电联合运行下多种柔性负荷协调优化不足以及面临的风、光出力和柔性负荷等多种不确定性,文章提出了一种考虑柔性负荷下的虚拟电厂(virtual power plant,VPP)热电联合鲁棒优化调度方法。充分考虑可削减、可平移、可转移柔性负荷之间的协调互补性,分别以热/电负荷曲线标准差和系统综合运行成本最低为目标,建立了虚拟电厂热电联合双层协调优化运行模型,提高了多种柔性负荷协调优化效果;并采用鲁棒优化方法处理风、光出力和柔性负荷预测误差的不确定性,提高热电系统运行的鲁棒性。多种柔性负荷的协调优化增强了系统的灵活调节能力,使经济性更优,不同鲁棒系数下柔性负荷优化效果的对比,为适应不同需求情景下的决策者提供参考依据。算例分析验证了所提模型的有效性。

关键词: 虚拟电厂(VPP), 不确定性, 鲁棒优化, 柔性负荷, 热电联合运行

Abstract:

Aiming at the lack of coordination and optimization of multiple flexible loads under combined heat and power operation and the uncertainties faced by wind, solar power, and flexible loads, a robust optimization scheduling method for virtual power plant(VPP)combined heat and power considering flexible loads is proposed. Fully considering the coordination and complementarity among the reduction, translation and transferable flexible loads, the standard deviations of the thermal and electric load curves and the lowest comprehensive operating cost of the system are chosen to be the goals, and a dual-layer coordinated optimization operation model of virtual power plant combined heat and power is established, which may improve the coordination and optimization effect of multiple flexible loads. The prediction error uncertainty of wind and solar power and flexible load is dealt with by the robust optimization method to improve the system operation robustness. The coordination and optimization of multiple flexible loads enhance the system's flexible adjustment capabilities and make the economy better. The comparison of the optimization effects of flexible loads under different robustness coefficients provides a reference for decision makers in different demand scenarios. The analysis of an example verifies the effectiveness of the proposed model.

Key words: virtual power plant (VPP), uncertainty, robust optimization, flexible load, combined heat and power operation

中图分类号:

TM73

王志南, 张宇华, 黄珂, 王丛. 计及多种柔性负荷的虚拟电厂热电联合鲁棒优化调度模型[J]. 电力建设, 2021, 42(7): 1-10.

WANG Zhinan, ZHANG Yuhua, HUANG Ke, WANG Cong. Robust Optimal Scheduling Model of Virtual Power Plant Combined Heat and Power Considering Multiple Flexible Loads[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(7): 1-10.

图/表 14

图1 系统运行结构

Fig.1 System operation structure

图2 系统优化流程

Fig.2 System optimization process

图3 系统求解流程

Fig.3 System solution flow

表1 可控机组参数

Table 1 Parameters of controllable units

表2 可平移负荷参数

Table 2 Parameters of shiftable loads

表3 可转移负荷参数

Table 3 Parameters of transferable loads

表4 可削减负荷参数

Table 4 Parameters of reducible loads

表5 场景设置

Table 5 Setting of scenes

图4 不同场景下优化效果对比

Fig.4 Comparison of optimization effect in different scenarios

表6 不同场景下优化效果指标对比

Table 6 Comparison of performance indices of optimization under different scenarios

图5 柔性负荷优化前后效果对比

Fig.5 Comparison of effect before and after optimization of flexible load

图6 不同鲁棒系数下柔性负荷优化效果

Fig.6 Optimal configuration effect of flexible load under different robustness coefficients

表7 不同鲁棒系数下的优化效果对比

Table 7 Comparison of optimization effect under different robustness coefficients

图7 VPP热电联合运行功率优化

Fig.7 VPP combined heat and power operation power optimization diagram

参考文献 16

[1]	KORAKI D, STRUNZ K. Wind and solar power integration in electricity markets and distribution networks through service-centric virtual power plants[J]. IEEE Transactions on Power Systems, 2018, 33(1):473-485. doi: 10.1109/TPWRS.2017.2710481 URL
[2]	江叶峰, 熊浩, 胡宇, 等. 考虑电热综合需求响应的虚拟电厂优化调度[J]. 电力建设, 2019, 40(12):61-69.
	JIANG Yefeng, XIONG Hao, HU Yu, et al. Optimal dispatching of virtual power plants considering comprehensive demand response of electricity and heat loads[J]. Electric Power Construction, 2019, 40(12):61-69.
[3]	BABAEI S, ZHAO C Y, FAN L. A data-driven model of virtual power plants in day-ahead unit commitment[J]. IEEE Transactions on Power Systems, 2019, 34(6):5125-5135. doi: 10.1109/TPWRS.59 URL
[4]	张军六, 樊伟, 谭忠富, 等. 计及需求响应的气电互联虚拟电厂多目标调度优化模型[J]. 电力建设, 2020, 41(2):1-10.
	ZHANG Junliu, FAN Wei, TAN Zhongfu, et al. Multi-objective optimization model of gas-electricity interconnected virtual power plant considering demand response[J]. Electric Power Construction, 2020, 41(2):1-10.
[5]	耿世平, 牛东晓, 郭晓鹏, 等. 计及多能源柔性负荷调度的微能源网多目标演化博弈[J]. 电力建设, 2020, 41(11):101-115.
	GENG Shiping, NIU Dongxiao, GUO Xiaopeng, et al. Multi-objective evolutionary game of micro energy grid considering multi-energy flexible load scheduling[J]. Electric Power Construction, 2020, 41(11):101-115.
[6]	米增强, 张文彦, 贾雨龙. 柔性负荷虚拟电厂下冰蓄冷空调的优化控制策略[J]. 电力自动化设备, 2018, 38(11):15-20, 27.
	MI Zengqiang, ZHANG Wenyan, JIA Yulong. Optimal control strategy of ice storage air conditioning under flexible load virtual power plant[J]. Electric Power Automation Equipment, 2018, 38(11):15-20, 27.
[7]	王海冰, 戚永志, 王承民, 等. 考虑柔性负荷的两阶段随机优化调度模型[J]. 电网技术, 2018, 42(11):3669-3675.
	WANG Haibing, QI Yongzhi, WANG Chengmin, et al. Two-stage stochastic optimal scheduling model considering flexible load[J]. Power System Technology, 2018, 42(11):3669-3675.
[8]	卢锦玲, 於慧敏, 杨进. 计及风电输出相依结构和柔性负荷激励/补偿机制的随机调度策略[J]. 电网技术, 2017, 41(6):1793-1800.
	LU Jinling, YU Huimin, YANG Jin. Stochastic scheduling strategy considering wind power dependence structure and motivation-compensation mechanism of flexible load[J]. Power System Technology, 2017, 41(6):1793-1800.
[9]	张涛, 王成, 王凌云, 等. 考虑虚拟电厂参与的售电公司双层优化调度模型[J]. 电网技术, 2019, 43(3):952-961.
	ZHANG Tao, WANG Cheng, WANG Lingyun, et al. A bi-level optimal dispatching model of electricity retailers integrated with VPPs[J]. Power System Technology, 2019, 43(3):952-961.
[10]	邹云阳, 杨莉, 冯丽, 等. 考虑热负荷二维可控性的微网热电协调调度[J]. 电力系统自动化, 2017, 41(6):13-19.
	ZOU Yunyang, YANG Li, FENG Li, et al. Coordinated heat and power dispatch of microgrid considering two-dimensional controllability of heat loads[J]. Automation of Electric Power Systems, 2017, 41(6):13-19.
[11]	胡荣, 张宓璐, 李振坤, 等. 计及可平移负荷的分布式冷热电联供系统优化运行[J]. 电网技术, 2018, 42(3):715-721.
	HU Rong, ZHANG Milu, LI Zhenkun, et al. Optimal operation for CCHP system considering shiftable loads[J]. Power System Technology, 2018, 42(3):715-721.
[12]	周博, 吕林, 高红均, 等. 多虚拟电厂日前鲁棒交易策略研究[J]. 电网技术, 2018, 42(8):2694-2703.
	ZHOU Bo, LÜ Lin, GAO Hongjun, et al. Robust day-ahead trading strategy for multiple virtual power plants[J]. Power System Technology, 2018, 42(8):2694-2703.
[13]	刘一欣, 郭力, 王成山. 微电网两阶段鲁棒优化经济调度方法[J]. 中国电机工程学报, 2018, 38(14):4013-4022.
	LIU Yixin, GUO Li, WANG Chengshan. Economic dispatch of microgrid based on two stage robust optimization[J]. Proceedings of the CSEE, 2018, 38(14):4013-4022.
[14]	孙国强, 周亦洲, 卫志农, 等. 能量和旋转备用市场下虚拟电厂热电联合调度鲁棒优化模型[J]. 中国电机工程学报, 2017, 37(11):3118-3128.
	SUN Guoqiang, ZHOU Yizhou, WEI Zhinong, et al. Thermal and electrical scheduling of a virtual power plant for participating in energy and spinning reserve markets based on robust optimization[J]. Proceedings of the CSEE, 2017, 37(11):3118-3128.
[15]	袁桂丽, 王琳博, 王宝源. 基于虚拟电厂“热电解耦”的负荷优化调度及经济效益分析[J]. 中国电机工程学报, 2017, 37(17):4974-4985.
	YUAN Guili, WANG Linbo, WANG Baoyuan. Optimal dispatch of heat-power load and economy benefit analysis based on decoupling of heat and power of virtual power plant[J]. Proceedings of the CSEE, 2017, 37(17):4974-4985.
[16]	许周, 孙永辉, 谢东亮, 等. 计及电/热柔性负荷的区域综合能源系统储能优化配置[J]. 电力系统自动化, 2020, 44(2):53-59.
	XU Zhou, SUN Yonghui, XIE Dongliang, et al. Optimal configuration of energy storage for integrated region energy system considering power/thermal flexible load[J]. Automation of Electric Power Systems, 2020, 44(2):53-59.