摘要
优化配煤对Texaco水煤浆加压气化装置的优化运行具有重要的意义。针对Texaco水煤浆气化装置优化配煤问题,建立了一个管理决策级视角下的配煤优化模型。模型综合考虑了混煤指标、库存成本、市场价格、操作成本、堆存和转运消耗。采用预交叉差分进化粒子群优化算法对模型进行求解,算法将粒子群和差分进化相结合,避免算法早熟,提高了全局搜索能力和收敛精度。最后,以某化肥厂水煤浆配煤优化过程为研究实例进行仿真,计算结果验证了模型和算法的可行性。
Coal blending optimization is of great significance for the optimal operation of Texaco coal gasification process.A process model from a management and decision-making perspective is constructed to solve the problem of Texaco coal blending optimization.The model takes into account mixed-coal indicators,inventory costs,market prices,operating costs and consumptions of stockpiling and transit.The model is calculated with particle swarm optimization with prior crossover differential evolution(PSOPDE),which can avoid prematurity more easily than basic PSO and DE,and has superior features in solution accuracy and efficiency. The simulation results of a coal blending optimal process of a fertilizer plant validate the feasibility of the model and algorithms.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2010年第8期1965-1970,共6页
CIESC Journal
基金
国家高技术研究发展计划项目(2009AA04Z141)
上海市基础研究重点项目(08JC1408200)~~
关键词
TEXACO气化炉
配煤
优化模型
粒子群算法
差分进化
Texaco gasifier
coal blending
optimization model
particle swarm optimization
differential evolution