提出将光伏剩余电量按照可变比例分配给储能电池及市政电网的动态运行策略,建立基于该策略的并网太阳能分布式供能系统设计运行联合优化模型,在不同分时电价下基于遗传算法对模型寻优,并将动态运行策略与对照运行策略（剩余电量优先并网或优先分配储能电池）下的系统运行结果进行比较分析。以陕西某乡村典型民居建筑为例进行分析,结果表明：1）分时电价的峰谷价差较大时,动态运行策略可有效降低太阳能分布式供能系统成本;2）分时电价的峰谷价差对于动态运行策略下储能电池的容量配置具有较大影响：峰谷价差越大,储能电池的配置容量越大;3）光伏度电补贴对3种运行策略下的系统成本影响程度为：动态运行策略>策略B（剩余电量优先分配储能电池）>策略A（剩余电量优先并网）。
Abstract
This research proposes a dynamic operation strategy that allocates photovoltaic surplus electricity to energy storage batteries and municipal grids in a variable proportion, and establishes a joint optimization model for the design and operation of grid-connected solar distributed energy supply systems based on this strategy, the model is optimized based on the genetic algorithm under different time-of-use electricity prices, and the system operation results under the dynamic operation strategy and the control operation strategy （the remaining power is connected to the grid first or the energy storage battery is allocated first） are compared and analyzed. Taking a typical residential building in a village in Shaanxi as an example, the results show that： 1）When the peak-to-valley price difference of the time-of-use electricity price is large, the dynamic operation strategy can effectively reduce the cost of solar distributed energy supply system; 2）The peak-to-valley price difference of the time-of-use electricity price is relatively dynamic, the capacity configuration of the energy storage battery under the operating strategy has a greater impact： the greater the peak-to-valley price difference, the greater the configuration capacity of the energy storage battery; 3）The impact of photovoltaic kilowatt-hours subsidies on the system cost under the three operating strategies is： dynamic operating strategy>Strategy B （remaining power is allocated to energy storage batteries first）>Strategy A （remaining power is first connected to the grid）.
关键词
太阳能分布式供能系统 /
设计运行联合优化 /
动态运行策略 /
储能电池 /
遗传算法 /
热电耦合
Key words
solar distributed energy supply system /
design and operation optimization /
dynamic operation strategy /
energy storage battery /
genetic algorithm /
thermoelectric coupling
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参考文献
[1] 王亚星. 基于动态运行策略的乡村民居建筑能源系统优化研究[D]. 西安: 西安建筑科技大学, 2021.
WANG Y X.Research on energy system optimization of rural residential buildings based on dynamic operation strategy[D]. Xi’an: Xi’an University of Architecture and Technology, 2021.
[2] 高孝天, 凌志斌, 郭海峰, 等. 基于粒子群优化的风储配合控制策略研究[J]. 太阳能学报, 2014, 35(11): 2249-2256.
GAO X T, LING Z B, GUO H F, et al.Research on wind storage coordination control strategy based on particle swarm optimization[J]. Acta energiae solaris sinica, 2014, 35(11): 2249-2256.
[3] 王志光, 杨希刚, 王玉璋, 等. 多能耦合的冷热电联供系统策略分析和优化设计[J]. 热能动力工程, 2019, 34(7): 9-14, 44.
WANG Z G, YANG X G, WANG Y Z, et al.Strategy analysis and optimal design of a multi-energy coupling combined cooling, heating and power system[J]. Thermal energy and power engineering, 2019, 34(7): 9-14, 44.
[4] 徐敏姣, 徐青山, 蒋菱. 基于太阳能空调的冷热电联供系统多目标优化运行研究[J]. 现代电力, 2017, 34(3): 60-68.
XU M J, XU Q S, JIANG L.Research on multi-objective optimization operation of combined cooling, heating and power system based on solar air-conditioning[J]. Modern electric power, 2017, 34(3): 60-68.
[5] BUORO D, CASISI M, PINAMONTI P, et al.Optimal lay-out and operation of district heating and cooling distributed trigeneration systems[C]// ASME Turbo Expo 2010: Power for Land, Sea, and Air, Glasgow, UK, 2010.
[6] 刘星月, 吴红斌. 太阳能综合利用的冷热电联供系统控制策略和运行优化[J]. 电力系统自动化, 2015, 39(12): 1-6.
LIU X Y, WU H B.Control strategy and operation optimization of combined heat and power system for solar energy comprehensive utilization[J]. Power system automation, 2015, 39(12): 1-6.
[7] MAGO P J, CHAMRA L M.Analysis and optimization of CCHP systems based on energy, economical, and environmental considerations[J]. Energy & Buildings, 2009, 41(10): 1099-1106.
[8] 邱雨微, 郑徐跃, 詹翔燕,等. 耦合可再生能源的分布式联供系统设计及运行策略优化[J]. 厦门大学学报(自然科学版), 2019, 58(1): 110-117.
QIU Y W, ZHENG X Y, ZHAN X Y, et al.Design and operation strategy optimization of distributed cogeneration system coupled with renewable energy[J]. Journal of Xiamen University(natural science edition), 2019, 58(1): 110-117.
[9] 熊焰, 吴杰康, 王强, 等. 风光气储互补发电的冷热电联供优化协调模型及求解方法[J]. 中国电机工程学报, 2015, 35(14): 3616-3625.
XIONG Y, WU J K, WANG Q, et al.Optimization and coordination model and solution method of combined cooling, heating and power generation of wind, solar and gas storage complementary power generation[J]. Proceedings of the CSEE, 2015, 35(14): 3616-3625.
[10] 刘艳峰, 王登甲. 太阳能采暖设计原理与技术[M]. 北京: 中国建筑工业出版社, 2016.
LIU Y F, WANG D J.Design principle and technology of solar heating[M]. Beijing: China Building Industry Press, 2016.
[11] DHAKER A, ANDRE M, GERARD C.Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems[J]. Mathematics and computers in simulation, 2014, 98: 46-62.
[12] 刘柏良. 多源微网典型应用的优化设计[D]. 南京: 东南大学, 2015.
LIU B L.Optimal design of typical applications of multi-source microgrid[D]. Nanjing: Southeast University, 2015.
[13] 张华俊, 王震, 陈小康, 等. 空气源热泵热水器变工况的实验研究[J]. 制冷空调与电力机械, 2009, 30(3): 1-4.
ZHANG H J, WANG Z, CHEN X K, et al.Experimental study on variable operating conditions of air source heat pump water heaters[J]. Refrigeration, air conditioning and electrical machinery, 2009, 30(3): 1-4.
[14] 姜益强, 姚杨, 马最良. 空气源热泵结霜除霜损失系数的计算[J]. 暖通空调, 2000, 30(5): 24-26.
JIANG Y Q, YAO Y, MA Z L.Calculation of frost and defrost loss coefficient of air source heat pump[J]. Journal of HVAC, 2000, 30(5): 24-26.
[15] 冯为民. 工程经济学[M]. 北京: 北京大学出版社, 2012.
FENG W M.Engineering economics[M]. Beijing: Peking University Press, 2012.
[16] 张晶晶. 独立型风光柴储微电网容量优化配置研究[D]. 保定: 华北电力大学, 2018.
ZHANG J J.Research on capacity optimization configuration of micro wind power grid for independent wind and diesel storage[D]. Baoding: North China Electric Power University, 2018.
[17] 郭放, 张俊月, 田原, 等. 太阳能采暖系统储热水箱体积匹配研究[J]. 太阳能学报, 2020, 41(9): 219-226.
GUO F, ZHANG J Y, TIAN Y, et al.Research on volume matching of hot water storage tank in solar heating system[J]. Acta energiae sdaris sinica, 2020, 41(9): 219-226
基金
国家自然科学基金青年项目（52008328）; 陕西省重点研发计划（2018ZDCXL-SF-03-01）
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