提升风能消纳清洁供热项目的经济性优化配置

在中国三北地区,热电联产机组"以热定电"的运行调节模式是供暖季出现严重弃风的重要原因之一.推进电供热、配置蓄热设备是促进风电消纳、降低系统能耗的有效方式.为实现清洁供热项目的经济性最优,提出了一种基于遗传算法和传统机组组合的双层优化模型.首先,在分析热、电能源供需的基础上,给出了区域能源系统的典型结构;然后,将日内净收益作为经济性优化的定量评价指标;通过分析能源系统的短期优化调度方式,得到最终的双层优化模型.在该模型中,外层优化利用遗传算法对不同的配置组合情况进行全局搜索,内层优化则通过求解线性规划给出特定组合条件下清洁供热项目的日内净收益.案例分析表明,清洁供热项目的经济性最优配置与区域能源系统的热、电负荷、风电出力特性和社会经济条件有关;同时,遗传算法可稳定收敛到全局最优点附近,优化计算结果完全满足工程应用的要求.另外,虽然清洁供热改造能够显著降低系统的弃风量,但出于经济性考虑,弃风并不能完全消除.

Economical planning of clean heating project to enhance wind energy accommodation

In three-north regions of China, power regulating abilities of cogeneration units are constrained significantly by their compulsory heat outputs. Such regulation mode is one of the key reasons for the large amounts of wind curtailment in the last few years in winter. Introducing electric heating boilers and thermal energy devices are effective ways to promote wind power integration and reduce the energy consumption of district heat and power system. In order to get the optimal economic configurations of the clean heating reconstruction projects, a two-layer optimization model based on the genetic algorithms and traditional unit commitments is proposed in this paper. First, by analysing the supply and demand relationship of heat and power, a typical structure of the district energy system (DES) in northern China was given. Then, the daily net benefits were defined as the quantitative economic indexes for any reconstruction projects. Finally, the two-layer optimization model was obtained by integrating short-term dispatch models of the DES. In this model, the genetic algorithms are used to search for the most economical configuration combinations globally, and the fitness values of the population are solved by the inner linear programming. Case studies indicate that the optimal configurations of the clean heating project were affected by several factors including the heat and power demands, characteristic of the wind power outputs, and socioeconomic conditions. Although differences exist between several independent genetic optimizations, any of these solutions are good enough to meet the requirements of engineering application. In addition, although more wind power can be integrated by introducing electric heating boilers and thermal energy devices, there is no need to integrate all wind power because of the law of diminishing return.