耦合电网约束的水电系统短期发电调度研究
Study on Short-Term Scheduling of Hydropower System Coupling Grid Constraint

DOI: 10.12677/JWRR.2016.53026, PP. 200-210

Keywords: 电网损耗，短期调度，水电系统，并行
Grid Loss, Short-Term Scheduling, Hydropower System, Parallel

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Abstract:

电网是水电站电力送出的必经途径，但在输送过程中不可避免地产生一定程度的电力损耗。以往研究大多集中在发电侧的水电站(群)发电量或发电效益最大，未能给予电力损耗充分的重视。因此，本文构建了考虑电网损耗的水电系统发电调度模型，以期实现水电最大化的消纳。同时，针对传统方法的早熟收敛缺陷，提出了耦合遗传算法和离散微分动态规划的离散微分遗传算法(DDGA)，并采用Fork/Join多核框架实现DDGA的并行求解，以求提高算法的搜索性能与求解效率。澜沧江流域梯级应用实例表明：所提模型与DDGA方法能够快速获得计及电网损耗的优化调度结果，有效提高电网水电消纳能力，具有较强的可行性及实用性。
The power grid is the only way of transmitting hydropower generation, and it will inevitably produce a certain degree of power loss in the transport process. Most previous studies focused on the generation side of maximum power out or generation benefits, without giving adequate attention to the power loss. In this paper, a short-term generation scheduling model coupling with power grid constraints is established, with the objective of maximizing the generation at the receiving end. A DDGA algorithm is proposed to solve the model, which combines the advantages of DDDP and GA. Moreover, based on the multi- core computer platform and Fork/Join parallel framework, a parallel processing method is used to improve the efficiency of solving the method. A case study of Lancang River cascade hydropower system proves that the model and DDGA method can quickly obtain optimal scheduling results, and it can improve the absorptive capacity of hydropower grid effectively. The proposed method is reasonability and practicability.

References

[1]	纪昌明, 李继伟, 张新明, 等. 梯级水电站短期发电优化调度的免疫蛙跳算法应用研究[J]. 水力发电学报, 2015, 34(1): 29-36. JI Changming, LI Jiwei, ZHANG Xinming, et al. Application of immune-shuffled frog-leaping algorithm to optimized operation of cascade hydropower stations for short-term power generation. Journal of Hydroelectric Engineering, 2015, 34(1): 29-36. (in Chinese)
[2]	申建建, 程春田, 李卫东, 等. 复杂时段耦合型约束水电站群短期变尺度优化调度方法[J]. 中国电机工程学报, 2014, 34(1): 87-95. SHEN Jianjian, CHENG Chuntian, LI Weidong, et al. A mutative-scale optimization method for short-term operation of hy-dropower plants with complex temporal coupling constraints. Proceedings of the CSEE, 2014, 34(1): 87-95. (in Chinese)
[3]	贾江涛, 管晓宏, 翟桥柱. 考虑水头影响的梯级水电站群短期优化调度[J]. 电力系统自动化, 2009, 33(13): 13-16. JIA Jiangtao, GUAN Xiaohong and ZHAI Qiaozhu. Short-term optimal scheduling of head-dependent cascaded hydropower stations. Automation of Electric Power Systems, 2009, 33(13): 13-16.
[4]	马超. 耦合航运要求的三峡–葛洲坝梯级水电站短期调度快速优化决策[J]. 系统工程理论与实践, 2013, 33(5): 1345- 1350. MA Chao. Fast optimal decision of short-term dispatch of three gorges and Gezhouba cascade hydropower stations with navi-gation demand considered. Systems Engineering Theory & Practice, 2013, 33(5): 1345-1350. (in Chinese)
[5]	胡国强. 梯级水电站优化调度模型与算法研究[D]: [博士学位论文]. 北京: 华北电力大学(北京), 2007. HU Guoqiang. Study on optimal scheduling model and algorithm of cascaded hydroelectric power plants. Beijing: North China Electric Power University (Beijing), 2007. (in Chinese)
[6]	邹进, 张勇传. 三峡梯级电站短期优化调度的模糊多目标动态规划[J]. 水利学报, 2005, 36(8): 925-931. ZOU Jin, ZHANG Yongchuan. Short-term optimal scheduling of cascade hydropower stations using fuzzy multi-objective dy-namic programming. Journal of Hydraulic Engineering, 2005, 36(8): 925-931. (in Chinese)
[7]	申建建, 武新宇, 程春田, 等. 大规模水电站群短期优化调度方法Ⅱ: 高水头多振动区问题[J]. 水利学报, 2011, 42(10): 1168-1176. SHEN Jianjian, WU Xinyu, CHEN Chuntian, et al. Comprehensive approach for classification of river systems and identification of ecological characteristics II. Applications. Journal of Hydraulic Engineering, 2011, 42(10): 1168-1176. (in Chinese)
[8]	武新宇, 程春田, 李刚, 等. 水电站群长期典型日调峰电量最大模型研究[J]. 水利学报, 2012, 43(3): 363-371. WU Xinyu, CHENG Chuntian, LI Gang, et al. Research on long term typical day peak load regulation energy maximization model for hydropower systems. Journal of Hydraulic Engineering, 2012, 43(3): 363-371. (in Chinese)
[9]	张忠波, 吴学春, 张双虎, 等. 并行动态规划和改进遗传算法在水库调度中的应用[J]. 水力发电学报, 2014, 33(4): 21-27. ZHANG Zhongbo, WU Xuechun, ZHANG Shuanghu, et al. Parallel dynamic programming and improved genetic algorithm and their application to reservoir operation. Journal of Hydroelectric Engineering, 2014, 33(4): 21-27. (in Chinese)
[10]	马宁. 水电站短期发电调度实用化模型及应用研究[D]: [硕士学位论文]. 大连: 大连理工大学, 2011. MA Ning. Hydro power station short-term scheduling practical modal and application research. Dalian: Dalian University of Technology, 2011. (in Chinese)
[11]	王金文, 刘双全. 短期水电系统发电调度的优化方法综述[J]. 水电能源科学, 2008, 26(6): 137-143. WANG Jinwen, LIU Shuangquan. Optimization techniques in short-term hydropower scheduling: A state-of-art review. Water Resources and Power, 2008, 26(6): 137-143. (in Chinese)
[12]	邵军. 一种理论线损计算的电量潮流法[D]: [硕士学位论文]. 大连: 大连理工大学, 2004. SHAO Jun. A power flow method for theoretical calculation of line loss. Dalian: Dalian University of Technology, 2011. (in Chinese)
[13]	申学滨. 电力线路损耗分析与计算方法比较[J]. 中国电力教育, 2014(3): 248-249. SHEN Xuebin. Comparison of power line loss analysis and calculation methods. China Electric Power Education, 2014(3): 248-249. (in Chinese)
[14]	RUDOLPH, G. Convergence analysis of canonical genetic algorithms. IEEE Transactions on Neural Networks, 1994, 5(1): 96- 101. http://dx.doi.org/10.1109/72.265964
[15]	LEA, D. A Java fork/join framework. Proceedings of the ACM 2000 Conference on Java Grande, 2000, 36-43. http://dx.doi.org/10.1145/337449.337465

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