考虑风荷不确定性的大用户直购电鲁棒区间优化调度

万庆祝; 刘伟娜

doi:10.19912/j.0254-0096.tynxb.2020-1169

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (7) : 347-355. DOI: 10.19912/j.0254-0096.tynxb.2020-1169

考虑风荷不确定性的大用户直购电鲁棒区间优化调度

万庆祝¹, 刘伟娜²

作者信息 +

DIRECT POWER PURCHASE BY LARGE CONSUMERS CONSIDERING WIND LOAD UNCERTAINTY ROBUST INTERVAL OPTIMAL SCHEDULING

Wan Qingzhu¹, Liu Weina²

Author information +

文章历史 +

摘要

该文以发电企业运行效益最优为目标,使用鲁棒区间优化方法对风电出力进行建模,用基于价格的需求响应对负荷不确定进行建模,建立考虑风电和负荷不确定性的大用户直购电鲁棒区间优化调度模型。最后,通过Matlab和CPLEX求解目标函数,验证所提模型的有效性和可行性。

Abstract

In order to optimize the operation efficiency of power generation enterprises, this paper uses the robust interval optimization method to model the wind power output, uses the price based demand response to model the load uncertainty, and establishes the robust interval optimization adjustment model for large consumers’ direct purchase of power considering the uncertainty of wind power and load. Finally, MATLAB and CPLEX are used to solve the objective function to verify the effectiveness and feasibility of the proposed model.

导出引用

万庆祝, 刘伟娜. 考虑风荷不确定性的大用户直购电鲁棒区间优化调度[J]. 太阳能学报. 2022, 43(7): 347-355 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1169

Wan Qingzhu, Liu Weina. DIRECT POWER PURCHASE BY LARGE CONSUMERS CONSIDERING WIND LOAD UNCERTAINTY ROBUST INTERVAL OPTIMAL SCHEDULING[J]. Acta Energiae Solaris Sinica. 2022, 43(7): 347-355 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1169

中图分类号： TM73

参考文献

[1] 夏清, 白杨, 钟海旺, 等. 中国推广大用户直购电交易的制度设计与建议[J]. 电力系统自动化, 2013, 37(20): 1-7.
XIA Q, BAI Y, ZHONG H W, et al.Institutional design and suggestions for promoting of direct electricity purchase by of large consumers in China[J]. Automation of electric power systems, 2013, 37(20): 1-7.
[2] 陈皓勇, 张森林, 张尧. 电力市场中大用户直购电交易模式及算法研究[J]. 电网技术, 2008, 31(21): 85-90.
CHEN H Y, ZHANG S L, ZHANG Y.Research on transaction mode of direct power purchase by large consumers in electricity market[J]. Power system technology, 2008, 32(21): 85-90.
[3] 周明, 郑雅楠, 李庚银, 等. 考虑分时电价和电能质量的大用户转运费用固定成本的综合分摊方法[J]. 中国电机工程学报, 2008, 28(19): 125-130.
ZHOU M, ZHENG Y N, LI G Y, et al.Synthetical method for allocating wheeling fixed cost for large consumers considering time-of-use pricing and power quality[J]. Proceedings of the CSEE, 2008, 28(19): 125-130.
[4] 王雁凌, 刘诗宁. 基于等利润率变化率的大用户直接交易合同电价模型[J]. 电网技术, 2013, 37(8): 2322-2327.
WANG Y L, LIU S N.Electricity price model of direct transaction contract for large power consumers based on equivalent change rate of profit margin[J]. Power system technology, 2013, 37(8): 2322-2327.
[5] 张宗益, 亢娅丽, 郭兴磊. 基于谱风险度量的大用户直购电组合模型分析[J]. 电工技术学报, 2013, 28(1): 266-270, 284.
ZHANG Z Y, KANG Y L, GUO X L.Model analysis of large consumers’power purchase portfolio based on spectral measuers of risk[J]. Transactions of China Electrotechnical Society, 2013, 28(1): 266-270, 284.
[6] 鲁皓, 林荫华. 基于双曲型谱风险度量的大用户购电策略[J]. 运筹与管理, 2018, 27(4): 138-143.
LU H, LIN Y H.Big users’electricity purchasing strategy based on hyperbolic spectrum risk measure[J]. Operations research and management science, 2018, 27(4): 138-143.
[7] 冯涛, 卢志刚, 李学平, 等. 考虑大用户直购电的动态环境经济调度[J]. 电工技术学报, 2016, 31(18): 151-159.
FENG T, LU Z G, LI X P, et al.Dynamic emission economic dispatch considering large consumers direct purchasing[J]. Transactions of China Electrotechnical Society, 2016, 31(18): 151-159.
[8] 田力丹, 张凯锋, 耿建, 等. 大用户直购电中鲁宾斯坦恩模型贴现因子的泛化分析[J]. 电力系统自动化, 2019, 43(15): 152-158.
TIAN L D, ZHANG K F, GENG J, et al.Generalization analysis on discount factor of rubinstein model for direct power purchase of large users[J]. Automation of electric power systems, 2019, 43(15): 152-158.
[9] 朱永胜, 乔百豪, 瞿博阳, 等. 含风电及电动汽车的多目标电力系统调度[J]. 太阳能学报, 2019, 40(6): 1722-1730.
ZHU Y S, QIAO B H, QU B Y, et al.Multi-objective power system dispatch with wind power and electric vehicles[J]. Acta energiae solaris sinica, 2019, 40(6): 1722-1730.
[10] 王爽心, 孙东旭, 刘如九. 基于小世界邻域PSO的含风场电力系统经济调度[J]. 太阳能学报, 2015, 36(11): 2823-2829.
WANG S X, SUN D X, LIU R J.Economic dispatch of wind farm integrated power system based on small world neighborhood PSO[J]. Acta energiae solaris sinica, 2015, 36(11): 2823-2829.
[11] 杨家然, 王兴成, 隋林涛, 等. 采用混合智能算法的含风电电力系统多目标优化调度[J]. 电力系统保护与控制, 2017, 45(11): 21-27.
YANG J R, WANG X C, SUI L T, et al.Multi-objective optimal scheduling of wind integrated power systems with hybrid intelligent algorithm[J]. Power system protection and control, 2017, 45(11): 21-27.
[12] NIKNAM T, AZIZIPANAH-ABARGHOOEE R, NARIMANI M R.An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation[J]. Applied energy, 2012, 99: 455-470.
[13] WANG Y S, LIU Y Z, KIRSCHEN S.Scenario reduction with submodular optimization[J]. IEEE transactions on power systems, 2017, 32(3): 2479-2480.
[14] 盛四清, 张立. 考虑风光荷预测误差的电力系统经济优化调度[J]. 电力系统及其自动化学报, 2017, 29(9): 80-85.
SHENG S Q, ZHANG L.Economic dispatch of power system considering the prediction error of wind power, solar energy and load[J]. Proceedings of the CSU-EPSA, 2017, 29(9): 80-85.
[15] 仲悟之, 黄思宇, 崔杨, 等. 考虑源荷不确定性的风电-光热-碳捕集虚拟电厂协调优化调度[J]. 电网技术2020, 44(9): 3424-3432.
ZHONG W Z, HUANG S Y, CUI Y, et al.W-S-C capture coordination in virtual power plant considering source-load uncertainty[J]. Power system technology, 2020, 44(9): 3424-3432.
[16] RAJENDRAN S, JENA D.Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control[J]. Journal of modern power systems and clean energy, 2014, 2(2): 114-125.
[17] LORCA Á, SUN X A.Multistage robust unit commitment with dynamic uncertainty sets and energy storage[J]. IEEE transactions on power systems, 2017, 32(3): 1678-1688.
[18] 张文韬, 王秀丽, 吴雄, 等. 大规模风电接入下含大用户直购电的电力系统调度模型研究[J]. 中国电机工程学报, 2015, 35(12): 2927-2935.
ZHANG W T, WANG X L, WU X, et al.An analysis model of power system with large-scale wind power and transaction mode of direct power purchase by large consumers involved in system scheduling[J]. Proceedings of the CSEE, 2015, 35(12): 2927-2935.
[19] 李言, 王秀丽, 张文韬, 等. 大用户直购电对系统风电消纳的影响[J]. 电工技术学报, 2017, 32(23): 149-157.
LI Y, WANG X L, ZHANG W T, et al.Impact of large consumers direct-purchasing on consumption of wind power of power systems[J]. Transactions of China Electrotechnical Society, 2017, 32(23): 149-157.
[20] 张倩文, 王秀丽, 杨廷天, 等. 大用户直购电模式下含大规模风光的电力系统优化调度[J]. 电力建设, 2017, 38(10): 24-32.
ZHANG Q W, WANG X L, YANG Y T, et al.Optimal dispatch of power system containing large scale wind-photovoltaic power with direct power purchase by large consumers[J]. Electric power construction, 2017, 38(10): 24-32.
[21] 邓强, 詹红霞, 杨孝华, 等. 考虑风电不确定性和大用户直购电的电力系统经济调度[J]. 电力系统保护与控制, 2019, 47(14): 131-139.
DENG Q, ZHAN H X, YANG X H, et al.Power system economic dispatching considering the uncertainty of wind power and large consumers direct purchasing[J] Power system protection and control, 2019, 47(14): 131-139.
[22] 崔明勇, 靳贺, 何良策, 等. 基于风电消纳评估的电力系统鲁棒低碳经济调度[J]. 太阳能学报, 2020, 41(8): 270-280.
CUI M Y, JIN H, HE L C, et al.Robust low-carbon economic dispatch of power system based on wind power accommodation evaluation[J]. Acta energiae solaris sinica, 2020, 41(8): 270-280.
[23] 艾欣, 周树鹏, 赵阅群. 考虑风电不确定性的用户侧分时电价研究[J]. 电网技术, 2016, 40(5): 1529-1535.
AI X, ZHOU S P, ZHAO Y Q.Study on time of use pricing of user side considering wind power uncertainty[J]. Power system technology, 2016, 40(5): 1529-1535.
[24] 董军, 聂麟鹏,聂仕麟, 等. 考虑需求响应与风电不确定性的两阶段鲁棒旋转备用容量优化模型[J]. 电力建设, 2019, 40(11): 55-64.
DONG J, NIE L P, NIE S L, et al.Two-stage robust optimization model for spinning reserve capacity considering demand response and uncertainty of wind power[J]. Electric power construction, 2019, 40(11): 55-64.
[25] 王秀云, 冯旭, 刘天琪, 等. 含用能权的风电电力系统低碳经济调度[J]. 太阳能学报, 2020, 41(1): 255-263.
WANG X Y, FENG X, LIU T Q, et al.A low-carbon economic dispatching for power grid integrated with wind power system considering right of using energy[J]. Acta energiae solaris sinica, 2020, 41(1): 255-263.
[26] 李斯, 周任军, 童小娇, 等. 基于盒式集合鲁棒优化的风电并网最大装机容量[J]. 电网技术, 2011, 35(12): 208-213.
LI S, ZHOU R J, TONG X J, et al.Robust optimization with box set for maximum installed capacity of wind farm connected to grid[J]. Power system technology, 2011, 35(12): 208-213.
[27] 邓强. 考虑风电预测误差的大用户直购电调度模型的研究[D]. 成都: 西华大学, 2019.
DENG Q.Study on direct power purchase scheduling model for large consumers considering wind power prediction error[D]. Chengdu: Xihua University, 2019.