干货｜电力体制改革背景下 电企如何售电以获取最大化利益？

其中调度模式1的调度模型是在本文调度模型的基础上去掉深度调峰的收益与成本函数以及约束条件,且所有的Z(t,s)=0;调度模式2是在本文调度模型的基础上去掉储热罐的运行成本函数与运行约束条件;调度模式3即为本文的调度模型。3种调度模式的对比结果如表7所示。

对比模式1和模式3的结果,热电厂参与两个市场获得的总收益高于只参与电能市场所获得的总收益,这是因为深度调峰市场的边际出清价格大部分情况下都高于电能市场的售电价格。模式1比模式3的偏差费用少的原因是热电厂提供深度调峰服务时其调节偏差的能力变弱,偏差主要靠储热罐调节,但偏差费用减少的幅度少于深度调峰补偿收益,所以模式3总收益更高。对比模式2和模式3,配置储热罐提高了热电厂的调峰能力,在降低偏差补偿的同时提升了深度调峰补偿收益和总收益。

5 结论

针对东北电力调峰辅助服务市场的运营规则,提出了基于两阶段随机规划的热电厂竞价策略,第一阶段以热电厂发电成本最小为目标求取出力初态以及参与深度调峰市场可获更高收益的时段;第二阶段以热电厂收益最大为目标,分配电能市场和深度调峰市场的投标电量。算例分析结果表明：

1）相比蒙特卡洛算法,拉丁超立方体算法生成的场景集,对原始数据的覆盖率更高、与历史数据更为接近,作为调度模型的输入更具参考意义。

2）由市场出清模型预估的中标电量与投标电量上限之间留有裕度,使得竞价策略鲁棒性较好。

3）相比于只参与电能市场,热电厂同时参与电能市场和深度调峰辅助服务市场可获更高收益,且通过配置储热罐可进一步提升收益。

参考文献

[1]国家能源局东北监管局.东北电力辅助服务市场专项改革试点工作正式启动[EB/OL].(2016-11-24)[2019-01-26]..

[2]国家能源局.电力辅助服务市场建设加速[EB/OL].(2018-05-23) [2019-01-26]..

[3]刘永奇,张弘鹏,李群,等.东北电网电力调峰辅助服务市场设计与实践[J].电力系统自动化,2017,41(10):148-154.LiuYongqi,ZhangHongpeng,LiQun,et al.Design and practice of peak regulation ancillary service market for Northeast China Power Grid[J].Automation of Electric Power Systems,2017,41(10):148-154(in Chinese).

[4]林俐,田欣雨.基于火电机组分级深度调峰的电力系统经济调度及效益分析[J].电网技术,2017,41(7):2255-2263.LinLi,TianXinyu.Analysis of deep peak regulation and its benefit of thermal units in power system with large scale wind power integrated[J].Power System Technology,2017,41(7):2255-2263(in Chinese).

[5]刘鹏.火电厂参与调峰辅助服务策略研究[J].东北电力技术,2018,39(4):34-37.LiuPeng.Research on coal fired generator participating in peak valley dispatching ancillary service strategy[J].Northeast Electric Power Technology,2018,39(4):34-37(in Chinese).

[6]李平,赵适宜,金世军,等.基于热网与建筑物储热解耦的调峰能力提升方案[J].电力系统自动化,2018,42(13):20-28,42.LiPing,ZhaoShiyi,JinShijun,et al.Promotion method of peak regulation capacity by power and heat decoupling based on heat storage of district heating network and buildings[J].Automation of Electric Power Systems,2018,42(13):20-28,42(in Chinese).

[7]彭飞翔,李晓晶,孙辉,等.考虑发电集团利益主体协调的风电消纳调度策略[J].电力系统自动化,2018,42(18):98-108.PengFeixiang,LiXiaojing,SunHui,et al.Dispatch strategy for wind power accommodation considering coordination of power generation group stakeholders[J].Automation of Electric Power Systems,2018,42(18):98-108(in Chinese).

[8]苏鹏,王文君,杨光,等.提升火电机组灵活性改造技术方案研究[J].中国电力,2018,51(5):87-94.SuPeng,WangWenjun,YangGuang,et al.Research on the technology to improve the flexibility of thermal power plants[J].Electric Power,2018,51(5):87-94(in Chinese).

[9]Gazafroudi AS,SoaresJ,Ghazvini M A F.Stochastic interval-based optimal offering model for residential energy management systems by household owners[J].International Journal of Electrical Power & Energy Systems,2019,105(2):201-219.

[10]VerbicG,Canizares CA.Probabilistic optimal power flow in electricity markets based on a two-point estimate method[J].IEEE Transactions on Power Systems,2006,21(4):1883-1893.

[11]Renani YK,EhsanM,ShahidehpourM.Day-ahead self-scheduling of a transmission-constrained GenCo with variable generation units using the incomplete market information[J].IEEE Transactions on Sustainable Energy,2017,8(3):1260-1268.

[12]Su WC,Wang JH,RohJ.Stochastic energy scheduling in microgrids with intermittent renewable energy resources[J].IEEE Transactions on Smart Grid,2014,5(4):1876-1883.

[13]RajeshP,Prashant KT.Economic risk-based bidding strategy for profit maximization of wind-integrated day-ahead and real-time double-auctioned competitive power markets[J].IET Generation Transmission & Distribution,2019,13(2):209-218.

[14]ShiL,LuoY,Tu GY.Bidding strategy of microgrid with consideration of uncertainty for participating in power market[J].International Journal of Electrical Power & Energy Systems,2014,59(7):1-13.

[15]袁桂丽,王琳博,王宝源,等.基于虚拟电厂“热电解耦”的负荷优化调度及经济效益分析[J].中国电机工程学报,2017,37(17):4974-4985,5217.YuanGuili,WangLinbo,WangBaoyuan,et al.Optimal dispatch of heat-power load and economy benefit analysis based on decoupling of heat and power of virtual power plant[J].Proceedings of the CSEE,2017,37(17):4974-4985,5217(in Chinese).

[16]FazlalipourP,EhsanM,Mohammadi LB.Optimal participation of low voltage renewable micro-grids in energy and spinning reserve markets under price uncertainties[J].International Journal of Electrical Power & Energy Systems,2018,102(11):84-96.

[17]董雷,刘梦夏,陈乃仕,等.基于随机模型预测控制的分布式能源协调优化控制[J].电网技术,2018,42(10):3219-3227.DongLei,LiuMengxia,ChenNaishi,et al.Coordinated optimal control of distributed energy based on stochastic model predictive control[J].Power System Technology,2018,42(10):3219-3227(in Chinese).

[18]仉梦林,胡志坚,王小飞,等.基于动态场景集和需求响应的二阶段随机规划调度模型[J].电力系统自动化,2017,41(11):68-76.ZhangMenglin,HuZhijian,WangXiaofei,et al.Two-stage stochastic programming scheduling model based on dynamic scenario sets and demand response[J].Automation of Electric Power Systems,2017,41(11):68-76(in Chinese).

[19]PinsonP,GirardR.Evaluating the quality of scenarios of short-term wind power generation[J].Applied Energy,2012,96(8):12-20.

[20]国家能源局东北监管局.东北电力辅助服务市场运营规则(暂行)[Z].沈阳:国家能源局东北监管局,2019.

[21]艾欣,周树鹏,赵阅群,等.含虚拟发电厂的电力系统优化运行与竞价策略研究[J].中国电机工程学报,2016,36(23):6351-6362,6600.AiXin,ZhouShupeng,ZhaoYuequn,et al.Research on optimal operation and bidding strategy of power system with virtual power plants[J].Proceedings of the CSEE,2016,36(23):6351-6362,6600(in Chinese).

[22]Gao YJ,Zhou XJ,Ren JF,et al.Double layer dynamic game bidding mechanism based on multi-agent technology for virtual power plant and internal distributed energy resource[J].Energies,2018,11(11):3072.

[23]王锡凡,王秀丽,陈皓勇,等.电力市场基础[M].西安:西安交通大学出版社,2003:71-74.

[24]付亦殊,陈红坤,姜欣,等.促进大规模风电消纳的双层调峰补偿机制研究[J].电力系统保护与控制,2019,47(4):51-57.FuYishu,ChenHongkun,JiangXin,et al.A bi-layer peak-regulation compensation mechanism for large-scale wind power integration[J].Power System Protection and Control,2019,47(4):51-57(in Chinese).

[25]戴远航,陈磊,闵勇,等.风电场与含储热的热电联产联合运行的优化调度[J].中国电机工程学报,2017,37(12):3470-3479,3675.DaiYuanhang,ChenLei,MinYong,et al.Optimal dispatch for joint operation of wind farm and combined heat and power plant with thermal energy storage[J].Proceedings of the CSEE,2017,37(12):3470-3479,3675(in Chinese).

[26]NordPool.MCP_data_report[EB/OL].(2019-01-17)[2019-01-26].

[27]www.ndrc.gov.cn/zwfwzx/zfdj/jggg/201512/t20151230_769630.html.