摘要
火电灵活性改造,特别是降低机组最小稳定功率,可有效增强系统调峰能力,缓解弃风弃光问题。但灵活调节需求随风光电源、负荷和电网运行特性动态变化而难以准确估计,火电厂易陷入过度投资或无序竞争的两难抉择而延迟乃至放弃改造,导致实际改造容量远低于国家规划预期。因此,如何在保证可再生能源消纳目标前提下科学规划火电机组的灵活性改造容量成为地区能源管理部门和火电厂共同关注的问题。首先建立了包括机组改造成本、调峰市场交易成本、售电收益损失、深调状态发电成本增量和系统弃电成本五部分费用在内的火电机组灵活性改造广义成本模型,基于随机生产模拟方法在中长期时间尺度下给出了机组年度发电量和广义成本计算方法。以全体火电机组灵活性改造广义成本最低为目标,建立了火电机组灵活性改造容量规划模型,并利用遗传算法求解所提优化模型。仿真算例验证了灵活性改造规划方法的可行性,同时分析了新能源电价等外部条件对规划结果的影响。
Flexibility transformation of thermal power,especially for reducing the minimum stable power of the unit to increase the downward adjustment capacity,can enhance the renewable energy accommodation.It is difficult to accurately estimate the demand of flexible regulation with the dynamic changes of wind power,load and power grid operation characteristics.Thermal power plants are easy to fall into the dilemma of excessive investment or disorderly competition and delay or even give up the transformation,resulting in the actual capacity of transformation far lower than the national planning.To effectively optimize the plan of flexibility transformation of thermal power units to enhance renewable energy consumption has become an important issue that need to be addressed by the regional energy management departments of power plants.This study comprehensively considers the transformation cost,peak regulation compensation,reduced electricity income,increased fuel consumption cost,and curtailment cost as the overall cost.Based on the probabilistic production of simulation method,various costs in the medium-and long-term perspective is calculated,where the change of energy generated before and after the transformation is revealed.This study aims at establishing the capacity planning model for the flexibility reformation of thermal unit,with the objective of the lowest overall cost of flexibility reformation.The model is solved using genetic algorithm.The simulation verifies that the proposed model can provide the units transformation scheme suitable for the planning stage and analyzes the impact of renewable power price and other costs.
作者
徐昊亮
靳攀润
姜继恒
鲁宗相
乔颖
XU Haoliang;JIN Panrun;JIANG Jiheng;LU Zongxiang;QIAO Ying(State Grid Gansu Electric Power Company Economy and Technology Research Institute,Lanzhou 730050,China;State Key Lab of Control and Simulation of Power Systems and Generation Equipment,(Dept.of Electrical Engineering,Tsinghua University),Haidian District,Beijing 100084,China)
出处
《全球能源互联网》
2020年第4期393-403,共11页
Journal of Global Energy Interconnection
基金
国网甘肃电力公司科技项目(SGGSJY00PSWT1700272)
国家重点研发计划项目(2017YFB0902200)。
关键词
灵活性改造
容量规划
随机生产模拟
遗传算法
flexibility transformation
capacity planning
probabilistic production simulation
genetic algorithm
