Rural Electricity-Heat Integrated Energy System Planning Based on Coupling Utilization of Biomass and Solar Resources

doi:10.12204/j.issn.1000-7229.2023.03.001

Abstract

Abstract:

Renewable energy sources such as solar energy and biomass energy are abundant in rural areas of China, but the energy utilization rate is low and pollution is serious. Aiming at the rural scene where clean renewable energy sources such as biomass and solar energy are connected, a multi-objective planning method based on the coupling utilization of biomass and solar power for rural electricity-heat integrated energy system is proposed, considering the transmission characteristics of heat network and the adjustable agricultural production load. Firstly, a typical architecture of rural integrated energy system is constructed considering the coupling utilization of biomass and solar energy resources. At the same time, the virtual energy storage function of thermal network, adjustable load of agricultural production and key equipment of the system are modeled and analyzed, and relevant operation strategies are proposed. Secondly, a planning and optimization model for rural integrated energy system is constructed, which takes into account economy, environmental protection and energy efficiency. Considering constraints such as investment capacity, equipment operation and energy balance, the Levy flight-based particle swarm optimization algorithm (LPSO) is used to solve the planning optimization scheme. Finally, the simulation is carried out in a village and town of a county in northern China, and the results show that the proposed method is reasonable and effective.

Key words: rural electricity-heat integrated energy system, biomass-solar coupling, virtual thermal energy storage, multi-objective

CLC Number:

TM715

WANG Yongli, HAN Xu, LIU Chen, CAI Chengcong, ZHOU Minhan, MA Ziben. Rural Electricity-Heat Integrated Energy System Planning Based on Coupling Utilization of Biomass and Solar Resources[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(3): 1-14.

Figures/Tables 17

Fig.1 Architecture of rural electricity-heat integrated energy system based on biomass-solar coupling

Fig.2 Diagram of thermal system structure

Fig.3 Transmission characteristics of thermal system

Fig.4 Energy-flow relationship of thermal generator sets

Fig.5 Flow chart of LPSO algorithm

Table 1 Basic data of equipment

Fig.6 Node structure of the heat network

Fig.7 Basic data

Fig.8 Comparison of algorithms

Fig.9 Three-dimension Pareto diagram

Table 2 Scene setup sheet

Table 3 All types of equipment under different scenarioskW

Table 4 Planning results under different scenarios

Fig.10 Typical daily basic data

Fig.11 Comparison of typical daily heating system output

Fig.12 Comparison of typical daily electricity system output

Table 5 Comparison of operating indicators in various scenarios

References 29

[1]	高阳, 席皛, 刘小慧, 等. 考虑生物质供给价格弹性的工业园区综合能源系统规划[J]. 电力建设, 2021, 42(4): 49-58. doi: 10.12204/j.issn.1000-7229.2021.04.006
	GAO Yang, XI Xiao, LIU Xiaohui, et al. Integrated energy system planning method for industrial parks considering the price elasticity of biomass supply[J]. Electric Power Construction, 2021, 42(4): 49-58. doi: 10.12204/j.issn.1000-7229.2021.04.006
[2]	程杉, 徐建宇, 何畅, 等. 计及不确定性的综合能源系统容量规划方法[J]. 电力系统保护与控制, 2021, 49(18): 17-24.
	CHENG Shan, XU Jianyu, HE Chang, et al. Optimal capacity planning of an integrated energy system considering uncertainty[J]. Power System Protection and Control, 2021, 49(18): 17-24.
[3]	MA T F, WU J Y, HAO L L, et al. The optimal structure planning and energy management strategies of smart multi energy systems[J]. Energy, 2018, 160: 122-141. doi: 10.1016/j.energy.2018.06.198 URL
[4]	HUANG Y, KANG J, LIU L, et al. A hierarchical coupled optimization approach for dynamic simulation of building thermal environment and integrated planning of energy systems with supply and demand synergy[J]. Energy Conversion and Management, 2022, 258: 115497. doi: 10.1016/j.enconman.2022.115497 URL
[5]	WANG Y L, WANG X H, YU H Y, et al. Optimal design of integrated energy system considering economics, autonomy and carbon emissions[J]. Journal of Cleaner Production, 2019, 225: 563-578. doi: 10.1016/j.jclepro.2019.03.025 URL
[6]	WANG Y L, LI R W, DONG H R, et al. Capacity planning and optimization of business park-level integrated energy system based on investment constraints[J]. Energy, 2019, 189: 116345. doi: 10.1016/j.energy.2019.116345 URL
[7]	王珺, 顾伟, 陆帅, 等. 结合热网模型的多区域综合能源系统协同规划[J]. 电力系统自动化, 2016, 40(15): 17-24.
	WANG Jun, GU Wei, LU Shuai, et al. Coordinated planning of multi-district integrated energy system combining heating network model[J]. Automation of Electric Power Systems, 2016, 40(15): 17-24.
[8]	邵世圻, 戴赛, 胡林献, 等. 计及热网特性的电热联合系统调度方法[J]. 电力系统保护与控制, 2018, 46(10): 24-30.
	SHAO Shiqi, DAI Sai, HU Linxian, et al. Research on heat-electricity combined scheduling method considering the characteristics of the heating network[J]. Power System Protection and Control, 2018, 46(10): 24-30.
[9]	董彧彤, 王艳松, 倪承波, 等. 计及用热舒适度弹性的热电联合优化调度[J]. 电力系统保护与控制, 2021, 49(23): 26-34.
	DONG Yutong, WANG Yansong, NI Chengbo, et al. Dispatch of a combined heat-power system considering elasticity with thermal comfort[J]. Power System Protection and Control, 2021, 49(23): 26-34.
[10]	吴琼, 吴彦琪, 任洪波, 等. 基于双向耦合的综合能源系统电热联合潮流计算[J]. 热力发电, 2021, 50(4): 14-22.
	WU Qiong, WU Yanqi, REN Hongbo, et al. Power flow calculation of combined electric and thermal for integrated energy system based on two-way coupling[J]. Thermal Power Generation, 2021, 50(4): 14-22.
[11]	杨莘博, 谭忠富, 薛帆, 等. “能源互联网+农村能源”典型场景、商业模式及成本价值核算研究[J]. 分布式能源, 2021, 6(3): 19-31.
	YANG Shenbo, TAN Zhongfu, XUE Fan, et al. Research on typical scenarios, business models and cost value accounting of “energy internet + rural energy”full text replacement[J]. Distributed Energy, 2021, 6(3): 19-31.
[12]	马令希, 付学谦. 考虑农业-气象-能源耦合的农业能源互联网理论及应用[J]. 中国电力, 2021, 54(11): 115-124.
	MA Lingxi, FU Xueqian. Theory and application of agricultural energy Internet considering coupling of agriculture, meteorology and energy[J]. Electric Power, 2021, 54(11): 115-124.
[13]	黄扬琪, 何伟, 赵伟哲, 等. 计及动态响应特征的农村综合能源系统分层调控[J]. 电力系统及其自动化学报, 2022, 34(2): 122-129.
	HUANG Yangqi, HE Wei, ZHAO Weizhe, et al. Hierarchical management for rural integrated energy system considering dynamic response characteristics[J]. Proceedings of the CSU-EPSA, 2022, 34(2): 122-129.
[14]	孙志鹏. 基于TRNSYS的北方农村地区多能源互补系统优化设计[J]. 节能技术, 2021, 39(2): 173-177.
	SUN Zhipeng. Optimization design of multi-energy complementary system in northern rural areas using TRNSYS[J]. Energy Conservation Technology, 2021, 39(2): 173-177.
[15]	陈伟, 路源, 何欣, 等. 计及风光就地消纳的设施农业产业园区综合能源系统多目标优化调度方法[J]. 电力建设, 2021, 42(7): 20-27. doi: 10.12204/j.issn.1000-7229.2021.07.003
	CHEN Wei, LU Yuan, HE Xin, et al. A multi-objective optimal scheduling method for integrated energy system of protected agricultural industrial park considering local consumption rate of wind and solar engery[J]. Electric Power Construction, 2021, 42(7): 20-27. doi: 10.12204/j.issn.1000-7229.2021.07.003
[16]	王婉璐, 杨莉, 王蕾, 等. 考虑供热网储热特性的电-热综合能源系统优化调度[J]. 电力系统自动化, 2018, 42(21): 45-52.
	WANG Wanlu, YANG Li, WANG Lei, et al. Optimal dispatch of integrated electricity-heat energy system considering heat storage characteristics of heating network[J]. Automation of Electric Power Systems, 2018, 42(21): 45-52.
[17]	PAN E S, LI H, WANG Z D, et al. Operation optimization of integrated energy systems based on heat storage characteristics of heating network[J]. Energy Science & Engineering, 2021, 9(2): 223-238.
[18]	HE C, DAI C X, WU L, et al. Robust network hardening strategy for enhancing resilience of integrated electricity and natural gas distribution systems against natural disasters[J]. IEEE Transactions on Power Systems, 2018, 33(5): 5787-5798. doi: 10.1109/TPWRS.59 URL
[19]	魏中辉, 付学谦, 周亚中, 等. 考虑农作物生理特性的农业园区能源互联网综合安全分析[J]. 电网技术, 2022, 46(9): 3406-3416.
	WEI Zhonghui, FU Xueqian, ZHOU Yazhong, et al. Comprehensive security analysis of park-level agricultural energy internet considering physiological characteristics of crops[J]. Power System Technology, 2022, 46(9): 3406-3416.
[20]	王维洲, 刘福潮, 杨建华, 等. 基于可时移农业负荷的光伏智慧农业大棚微型能源网优化调度[J]. 中国农业大学学报, 2018, 23(6): 160-168.
	WANG Weizhou, LIU Fuchao, YANG Jianhua, et al. Optimization of the micro energy grid of PV intelligent agricultural greenhouse based on time-shifting agricultural load[J]. Journal of China Agricultural University, 2018, 23(6): 160-168.
[21]	杨晓伟, 杨斌, 纪历. 农业电排灌负荷特性的优化研究[J]. 机电信息, 2019(12): 31, 34.
	YANG Xiaowei, YANG Bin, JI Li. Study on optimization of load characteristics of agricultural electric drainage and irrigation[J]. Mechanical and Electrical Information, 2019(12): 31, 34.
[22]	赵亮, 黎嘉明, 艾小猛, 等. 光伏出力随机性分量的提取和统计特性分析[J]. 电力系统自动化, 2017, 41(1): 48-56.
	ZHAO Liang, LI Jiaming, AI Xiaomeng, et al. Analysis on random component extraction and statistical characteristics of photovoltaic power[J]. Automation of Electric Power Systems, 2017, 41(1): 48-56.
[23]	王子铭. 基于建筑相变储能的CCHP型微能源网优化调度研究[D]. 吉林: 东北电力大学, 2021.
	WANG Ziming. Research on coordinated optimal scheduling of CCHP micro energy grid based on building phase change energy storage[D]. Jilin: Northeast Dianli University, 2021.
[24]	赵达维, 张文涛, 刘旭娜, 等. 光伏与混合储能配合的园区综合能源系统规划[J]. 电力系统及其自动化学报, 2019, 31(10): 88-95.
	ZHAO Dawei, ZHANG Wentao, LIU Xuna, et al. Planning for park-level integrated energy system based on cooperation between PV and hybrid energy storage[J]. Proceedings of the CSU-EPSA, 2019, 31(10): 88-95.
[25]	邵成成, 冯陈佳, 李丁, 等. 光热发电机组聚合模型及其在电力系统运行模拟中的应用[J]. 中国电机工程学报, 2020, 40(11): 3507-3516.
	SHAO Chengcheng, FENG Chenjia, LI Ding, et al. Clustered CSP model and its application in power system operation simulation[J]. Proceedings of the CSEE, 2020, 40(11): 3507-3516.
[26]	侯慧, 刘鹏, 黄亮, 等. 考虑不确定性的电-热-氢综合能源系统规划[J]. 电工技术学报, 2021, 36(S1): 133-144.
	HOU Hui, LIU Peng, HUANG Liang, et al. Planning of electricity-heat-hydrogen integrated energy system considering uncertainties[J]. Transactions of China Electrotechnical Society, 2021, 36(S1): 133-144.
[27]	许健, 施锦月, 张建华, 等. 基于生物质热电混合供能的城镇综合能源双层优化[J]. 电力系统自动化, 2018, 42(14): 23-31.
	XU Jian, SHI Jinyue, ZHANG Jianhua, et al. Bi-level optimization of urban integrated energy system based on biomass combined heat and power supply[J]. Automation of Electric Power Systems, 2018, 42(14): 23-31.
[28]	王庆喜, 郭晓波. 基于莱维飞行的粒子群优化算法[J]. 计算机应用研究, 2016, 33(9): 2588-2591.
	WANG Qingxi, GUO Xiaobo. Particle swarm optimization algorithm based on Levy flight[J]. Application Research of Computers, 2016, 33(9): 2588-2591.
[29]	梁田, 曹德欣. 基于莱维飞行的改进简化粒子群算法[J]. 计算机工程与应用, 2021, 57(20): 188-196. doi: 10.3778/j.issn.1002-8331.2006-0254
	LIANG Tian, CAO Dexin. Improved and simplified particle swarm optimization algorithm based on Levy flight[J]. Computer Engineering and Applications, 2021, 57(20): 188-196. doi: 10.3778/j.issn.1002-8331.2006-0254