| 引用本文: | 于婧,孙宏斌,沈欣炜.考虑储热装置的风电-热电机组联合优化运行策略[J].电力自动化设备,2017,37(6): |
| YU Jing,SUN Hongbin,SHEN Xinwei.Optimal operating strategy of integrated power system with wind farm, CHP unit and heat storage device[J].Electric Power Automation Equipment,2017,37(6): |
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| 摘要: |
| 基于日前供热负荷预测和风电出力预测，考虑储热装置运行机理，研究风电场与热电机组联合运行的优化方法。将含储热装置的热电厂和风电场组成一个发电利益集合体，在满足地区供热负荷和提升风电消纳的同时，通过调节热电机组和储热装置的出力最大化发电利益集合体的收益。考虑热电机组的热-电耦合特性和储热装置的运行约束，建立了日前调度模型并进行求解。在此基础上，考虑风电出力的随机性，建立了相应的随机优化模型。算例分析表明，考虑储热的风电-热电机组联合优化所获得的收益高于风电场和热电机组单独运行获得的总收益，并且可在现行“以热定电”运行机制下提高风电的消纳能力。同时采用随机优化模型能有效降低系统联合出力的不确定性，可较好地解决风功率预测中的不确定性问题。 |
| 关键词: 风电 热电联产 储热系统 随机优化 不确定性 |
| DOI：10.16081/j.issn.1006-6047.2017.06.019 |
| 分类号:TM761 |
| 基金项目:国家自然科学基金资助项目(51537006)；中国博士后科学基金一等面上资助项目(2016M60092) |
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| Optimal operating strategy of integrated power system with wind farm, CHP unit and heat storage device |
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YU Jing1, SUN Hongbin2, SHEN Xinwei1
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1.Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518000, China;2.State Key Lab of Control and Simulation of Power Systems and Generation Equipments, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
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| Abstract: |
| The optimal operating strategy of integrated power system with wind farm, CHP (Combined Heat and Power) unit and heat storage device is studied based on the day-ahead forecasts of heat load and wind power output. The thermal power plant with heat storage device and the wind farm are integrated as a power generation aggregator and its overall profit can be maximized by adjusting the outputs of CHP unit and heat storage device while meeting the district heat demand and enhancing wind power accommodation. A day-ahead scheduling model considering the heat-power coupling of CHP unit and the operational constraints of heat storage device is built and solved, based on which, a corresponding stochastic optimization model considering the randomness of wind power output is established. Case study shows that, with the coordinated optimization, the overall profit of integrated power system with wind farm, CHP unit and heat storage device increases and its wind power accommodation capability improves in “power-follow-heat” mode. Meanwhile, the stochastic optimization model solves the uncertainty problem of wind power prediction quite well to effectively reduce the uncertainty of system power output. |
| Key words: wind power combined heat and power heat storage system stochastic optimization uncertainty |
