在独立微电网中由于可调度能源不可用,仅考虑不可调度的风能和太阳能供应所需能量。通过可调度负荷的转移和调度来减少或消除发电与用电之间的不匹配,从而实现微电网组件容量优化和相关成本降低。此外,还研究需求响应对降低发电损失的影响。对是否计及需求响应两种情况的优化结果进行比较,对于每种情况确定了最佳配置。结果表明:需求响应的应用减少了电池数量、逆变器和光伏组件容量,从而降低了总净现值成本。同时,需求响应的实施降低了负荷峰值,提高了负荷系数和相关系数,验证了所提模型及方法的有效性。
Abstract
Since the schedulable energy is not available in the independent microgrid, only the energy required by the non schedulable wind and solar energy is considered. Through the transfer and scheduling of schedulable loads, the mismatch between power generation and power consumption can be reduced or eliminated, so as to optimize the capacity of microgrid components and reduce the related costs. In addition, the influence of demand response on reducing generation loss is studied. The optimization results of whether the demand response is taken into account are compared, and the optimal configuration is determined for each case. The results show that the application of demand response reduces the number of cells, inverter and photovoltaic panel capacity, thereby reducing the total net present value cost. At the same time, the implementation of demand response reduces the peak load, improves the load coefficient and correlation coefficient, and verifies the effectiveness of the proposed model and method.
关键词
微电网 /
需求响应 /
优化调度 /
技术经济优化 /
可再生能源
Key words
microgrid /
demand response /
optimal dispatching /
techno-economic optimization /
renewable energy
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参考文献
[1] 赵超, 王斌, 孙志新, 等. 基于改进灰狼算法的独立微电网容量优化配置[J]. 太阳能学报, 2022, 43(1): 256-262.
ZHAO C, WANG B, SUN Z X, et al.Optimal configuration optimization of islanded microgrid using improved grey wolf optimizer algorithm[J]. Acta energiae solaris sinica, 2022, 43(1): 256-262.
[2] 李翼翔, 田震, 唐英杰, 等. 考虑构网型与跟网型逆变器交互的孤岛微电网小信号稳定性分析[J]. 电力自动化设备, 2022, 42(8): 11-18.
LI Y X, TIAN Z, TANG Y J, et al.Small-signal stability analysis of island microgrid considering interaction between grid-forming converter and grid-following converter[J]. Electric power automation equipment, 2022, 42(8): 11-18.
[3] DHEER D K, VIJAY A S, KULKARNI O V, et al.Improvement of stability margin of droop-based islanded microgrids by cascading of lead compensators[C]//IEEE Transactions on Industry Applications. 2019: 3241-3251.
[4] 黄金鑫, 李华强, 陆杨. 基于蒙特卡洛模拟和频谱分析法的孤岛微电网储能容量配置[J]. 电网技术, 2020, 44(5): 1622-1629.
HUANG J X, LI H Q, LU Y.Energy storage capacity configuration of isolated microgrid based on Monte Carlo simulation and spectrum analysis[J]. Power system technology, 2020, 44(5): 1622-1629.
[5] 许德明, 李泽, 崔国增, 等. 孤岛微电网异构电池储能系统的分布式有限时间次级控制[J]. 控制与决策, 2021, 36(8): 2034-2041.
XU D M, LI Z, CUI G Z, et al.Distributed finite-time secondary control for heterogeneous battery energy storage systems in an islanded microgrid[J]. Control and decision, 2021, 36(8): 2034-2041.
[6] 李蕊睿, 李奇, 蒲雨辰, 等. 计及功率交互约束的含电-氢混合储能的多微电网系统容量优化配置[J]. 电力系统保护与控制, 2022, 50(14): 53-64.
LI R R, LI Q, PU Y C, et al.Optimal configuration of an electric-hydrogen hybrid energy storage multi-microgrid system considering power interaction constraints[J]. Power system protection and control, 2022, 50(14): 53-64.
[7] JIANG Y B, XU J, SUN Y Z, et al.Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system[J]. Applied energy, 2017, 190: 1126-1137.
[8] 谭颖, 吕智林, 李捷. 基于改进ELM的风/光/柴/储独立微电网分布式电源多目标容量优化配置[J]. 电力系统保护与控制, 2016, 44(8): 63-70.
TAN Y, LYU Z L, LI J.Multi-objective optimal sizing method for distributed power of wind-solar-diesel-battery independent microgrid based on improved electromagnetism-like mechanism[J]. Power system protection and control, 2016, 44(8): 63-70.
[9] LI B, WANG H L, TAN Z K.Capacity optimization of hybrid energy storage system for flexible islanded microgrid based on real-time price-based demand response[J]. International journal of electrical power & energy systems, 2022, 136: 107581.
[10] 李伟, 韩瑞迪, 孙晨家, 等. 基于用电偏好的可平移负荷参与需求响应最优激励合同与激励策略[J]. 中国电机工程学报, 2021, 41(增刊1): 185-193.
LI W, HAN R D, SUN C J, et al.An optimal incentive contract and strategy of shiftable loads participation in demand response based on user electricity preference[J]. Proceedings of the CSEE, 2021, 41(S1): 185-193.
[11] BEHBOODI S, CHASSIN D P, DJILALI N, et al.Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: a surplus maximizing approach[J]. Applied energy, 2017, 189: 336-351.
[12] WANG Y, LIN H Y, LIU Y L, et al.Management of household electricity consumption under price-based demand response scheme[J]. Journal of cleaner production, 2018, 204: 926-938.
[13] NILSSON A, LAZAREVIC D, BRANDT N, et al.Household responsiveness to residential demand response strategies: results and policy implications from a Swedish field study[J]. Energy policy, 2018, 122: 273-286.
[14] 马明, 刘涌. 计及住宅混合能源需求响应的含风电系统随机优化调度[J]. 太阳能学报, 2022, 43(1): 11-20.
MA M, LIU Y.Stochastic optimal dispatch of power system with wind power considering demand response of residential ahybrid energy system[J]. Acta energiae solaris sinica, 2022, 43(1): 11-20.
[15] 唐一铭, 赵双芝, 郭昭艺, 等. 基于负荷曲线等效斜率提升光伏消纳能力的需求响应策略[J]. 可再生能源, 2020, 38(12): 1626-1632.
TANG Y M, ZHAO S Z, GUO Z Y, et al.Demand response assisted photovoltaic absorption strategy considering the ramp rate limitation[J]. Renewable energy resources, 2020, 38(12): 1626-1632.
[16] 朱怡莹, 周荣生, 罗龙波. 考虑需求响应与光伏不确定性的电力系统经济调度[J]. 太阳能学报, 2023, 44(1): 62-68.
ZHU Y Y, ZHOU R S, LUO L B.Economic dispatch of power system considering demand response and PV uncertainty[J]. Acta energiae solaris sinica, 2023, 44(1): 62-68.
[17] CHAKRABORTY S, ARVIND P, KUMAR D.Coordinated control for frequency regulation in a stand-alone microgrid bolstering demand side management capability[J]. Electric power components and systems, 2021, 49(1/2): 1-17.
[18] REZKALLAH M, SINGH S, CHANDRA A, et al.Comprehensive controller implementation for wind-PV-diesel based standalone microgrid[J]. IEEE transactions on industry applications, 2019, 55(5): 5416-5428.
[19] WEN Y F, CHUNG C Y, LIU X, et al.Microgrid dispatch with frequency-aware islanding constraints[J]. IEEE transactions on power systems, 2019, 34(3): 2465-2468.