基于禁忌粒子群算法的热电联产负荷经济分配

Cogeneration economic dispatch based on taboo-particle swarm optimization algorithm

根据热电联产机组热电负荷可行域,建立含热电联产机组的负荷优化分配模型与全厂热电负荷可行域模型,将粒子群优化算法的全局搜索能力与禁忌算法的局部搜索能力相结合.对优化分配模型进行求解,在电负荷指令和热负荷指令分别为200 MW和115 MW下求解各机组负荷,总成本为2 695.2美元.通过算例分析验证了所提模型及算法的有效性,分析了凝汽式、热电联产式和纯供热机组之间的组合对全厂可行域的影响,并在此基础上分析了节能潜力与热电负荷指令的关系.

A cogeneration load dispatch model and whole plant＇s feasible region of heat and power load are proposed based on cogeneration units＇ feasible region. To solve the proposed model, a tabooparticle swarm optimization algorithm is presented. In this algorithm, the global searching ability of the particle swarm optimization algorithm and local searching ability of taboo algorithm are integrated to improve its accuracy and convergence speed. A case study is given with the power and heat load being 200 MW and 115 MW respectively, and each unit＇s load is proposed with the total cost of $ 2 695.2, which reveals the validity of proposed model and algorithm. The influence of combination of condensed steam unit, cogeneration unit and heat supply unit on whole plant＇s feasible region are analyzed. And the relationship between load command and energy saving potential are also analyzed.