Optimization Method of Generation Rights Transaction Mechanism for Power System Accommodation Improvement

doi:10.11930/j.issn.1004-9649.201907189

Abstract

Abstract: With renewable energy consumption becoming a key issue, generation rights transaction between wind power and captive plants plays an important role in improving the power system's accommodation capacity. But there is no theory for evaluating and optimizing such mechanisms in the medium and long term. Based on probabilistic production simulation, this paper proposes a medium and long-term evaluation model to calculate system's accommodation capacity rapidly. The main factors affecting accommodation effect are summarized after analysis of operation mode of generation rights transaction. Considering the probabilistic characteristics of load and various power sources, an assessment model is constructed. Then, the shaping effect of the power generation rights transaction on the wind power probability curve is discussed, followed by analyzing the relationship between wind curtailment reduction and three key parameters:transaction capacity, start-up wind power and daily transaction time. The simulation results validate the effectiveness of the proposed algorithm in quick optimization and efficiency evaluation in monthly and annual scale.

Key words: power generation rights transaction, probabilistic production simulation, probability characteristics, renewable energy accommodation, transaction optimization

XU Haoliang, JIN Panrun, JIANG Jiheng, LU Zongxiang, QIAO Ying. Optimization Method of Generation Rights Transaction Mechanism for Power System Accommodation Improvement[J]. Electric Power, 2020, 53(3): 167-176.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201907189

https://www.electricpower.com.cn/EN/Y2020/V53/I3/167

References

[1] IRENA: Renewable capacity statistics 2018[R]. 2018.
[2] 张正陵. 中国“十三五”新能源并网消纳形势、对策研究及多情景运行模拟分析[J]. 中国电力, 2018, 51(1): 2–9
ZHANG Zhengling. Research on situation and countermeasures of new energy integration in the 13th five-year plan period and its multi-scenario simulation[J]. Electric Power, 2018, 51(1): 2–9
[3] PEI W, DU Y, DENG W, et al. Optimal bidding strategy and intramarket mechanism of microgrid aggregator in real-time balancing market[J]. IEEE Transactions on Industrial Informatics, 2016, 12(2): 587–596.
[4] 胡朝阳, 毕晓亮, 王珂, 等. 促进负备用跨省调剂的华东电力调峰辅助服务市场设计[J]. 电力系统自动化, 2019, 43(5): 175–182
HU Zhaoyang, BI Xiaoliang, WANG Ke, et al. Design of peak regulation auxiliary service market for East China power grid to promote inter-provincial sharing of negative reserve[J]. Automation of Electric Power Systems, 2019, 43(5): 175–182
[5] MOISEEVA E, HESAMZADEH M R, BIGGAR D R. Exercise of market power on ramp rate in wind-integrated power systems[J]. IEEE Transactions on Power Systems, 2015, 30(3): 1614–1623.
[6] XU R H, SONG Z X, TANG Q F, et al. The cost and marketability of renewable energy after power market reform in China: a review[J]. Journal of Cleaner Production, 2018, 204: 409–424.
[7] 华夏, 罗凡, 张建华, 等. 促进新能源消纳的自备电厂发电权交易模式可行性探讨[J]. 电力系统自动化, 2016, 40(12): 200–206
HUA Xia, LUO Fan, ZHANG Jianhua, et al. Feasibility analysis of trade mode promoting new energy consumption based on generation rights trade of self-generation power plants[J]. Automation of Electric Power Systems, 2016, 40(12): 200–206
[8] 施泉生, 刘坤, 温蜜. 基于区块链技术的跨省发电权交易模型[J]. 电力建设, 2017, 38(9): 15–23
SHI Quansheng, LIU Kun, WEN Mi. Interprovincial generation rights trading model based on blockchain technology[J]. Electric Power Construction, 2017, 38(9): 15–23
[9] XUE B K, QI T X, ZHANG W, et al. Research on market bidding mechanism of generation rights trade for promoting new energy consumption[J]. The Journal of Engineering, 2017, 2017(13): 1378–1382.
[10] 何永秀, 宋栋, 夏天, 等. 基于合作博弈论的常规能源与新能源发电权置换交易模式研究[J]. 电网技术, 2017, 41(8): 2485–2490
HE Yongxiu, SONG Dong, XIA Tian, et al. Mode of generation right trade between renewable energy and conventional energy based on cooperative game theory[J]. Power System Technology, 2017, 41(8): 2485–2490
[11] 张显, 耿建, 庞博, 等. 发电权交易在中国节能减排中的应用及分析[J]. 电力系统自动化, 2014, 38(17): 87–90, 129
ZHANG Xian, GENG Jian, PANG Bo, et al. Application and analysis of generation right trade in energy-saving and emission reduction in China[J]. Automation of Electric Power Systems, 2014, 38(17): 87–90, 129
[12] LIU Y X, ZHANG N, KANG C, et al. Impact of carbon market on China's electricity market: an equilibrium analysis[C]//2017 IEEE Power & Energy Society General Meeting, July 16-20, 2017. Chicago, IL. IEEE, 2017: 1-5.
[13] LI S T, ZHANG S F, ANDREWS-SPEED P. Using diverse market-based approaches to integrate renewable energy: experiences from China[J]. Energy Policy, 2019, 125: 330–337.
[14] 王雁凌, 邱小燕, 许传龙. 以节能降耗为目标的发电权交易阻塞管理模型[J]. 电网技术, 2012, 36(6): 272–276
WANG Yanling, QIU Xiaoyan, XU Chuanlong. Congestion management of generation rights trade based on energy conservation[J]. Power System Technology, 2012, 36(6): 272–276
[15] 于昌海, 吴继平, 王运, 等. 适应发电权交易的可再生能源有功控制策略[J]. 电力系统自动化, 2017, 41(9): 71–76
YU Changhai, WU Jiping, WANG Yun, et al. Active power control strategy for renewable energy generation adapted to generation right trade[J]. Automation of Electric Power Systems, 2017, 41(9): 71–76
[16] 江岳文, 余代海. 面向“互联网+”的风火发电权交易促进风电接纳研究[J]. 太阳能学报, 2019, 40(1): 249–258
JIANG Yuewen, YU Daihai. Research on power generation right trading between wind farms and thermal units to promote accommodation of wind power through ‘internet+’[J]. Acta Energiae Solaris Sinica, 2019, 40(1): 249–258
[17] 李海波, 鲁宗相, 乔颖, 等. 基于非时序生产模拟的风电消纳评估方法[J]. 电力建设, 2015, 36(10): 129–137
LI Haibo, LU Zongxiang, QIAO Ying, et al. Evaluation method of wind power accommodation capacity based on non-sequential production simulation[J]. Electric Power Construction, 2015, 36(10): 129–137
[18] 吴少雷, 冯玉, 吴凯, 等. 基于交换卷积的含高比例新能源电力系统运行评估方法[J]. 中国电力, 2019, 52(4): 25–31
WU Shaolei, FENG Yu, WU Kai, et al. Operation evaluation method of high proportion renewable energy power system based on exchange convolution[J]. Electric Power, 2019, 52(4): 25–31
[19] LI Y, AGELIDIS V G, SHRIVASTAVA Y. Wind-solar resource complementarity and its combined correlation with electricity load demand[C]//2009 4th IEEE Conference on Industrial Electronics and Applications, May 25-27, 2009. Xi'an, China. IEEE, 2009: 3623-3628.
[20] ZHAO S J, XIE L, SINGH C. Cross-correlation study of onshore/offshore wind generation and load in Texas[C]//2013 North American Power Symposium (NAPS), September 22-24, 2013. Manhattan, KS, USA. IEEE, 2013: 1-5.
[21] 马彦宏, 姜继恒, 鲁宗相, 等. 基于随机生产模拟的火电机组深度调峰提升新能源消纳能力评估方法[J]. 全球能源互联网, 2019, 2(1): 35–43
MA Yanhong, JIANG Jiheng, LU Zongxiang, et al. Assessment method of conventional units with deep peak-shaving for renewable energy accommodation based on probabilistic production simulation[J]. Journal of Global Energy Interconnection, 2019, 2(1): 35–43