热力发电
熱力髮電
열력발전
THERMAL POWER GENERATION
2014年
11期
97-103
,共7页
王伟%常浩%苏宏业%石永锋
王偉%常浩%囌宏業%石永鋒
왕위%상호%소굉업%석영봉
火电厂%负荷优化分配%PSO-CE算法%环境成本%供电煤耗%污染物排放
火電廠%負荷優化分配%PSO-CE算法%環境成本%供電煤耗%汙染物排放
화전엄%부하우화분배%PSO-CE산법%배경성본%공전매모%오염물배방
thermal power plant%load optimal distribution%PSO-CE algorithm%environmental cost%coal con-sumption for power supply%pollutant emission
针对除尘、脱硫、脱硝改造后火电厂负荷优化分配问题,从提高全厂综合经济效益的角度出发,提出了一种考虑环境成本的全厂负荷优化分配模型和满足电网调度实时性要求的可控搜索粒子群优化(PSO-CE)算法。基于机组实际运行数据,构建了供电煤耗和多种污染物排放浓度特性模型,根据除尘、脱硫、脱硝补偿电价和排污费用标准,建立了面向最优综合经济效益的负荷优化分配模型和自适应负荷约束条件。在标准粒子群优化算法中引入可控随机搜索的速度因子和动态调整的最大速度限制因子,使其具有平衡算法的计算耗时和寻优能力,并通过某火电厂4台机组的负荷分配仿真试验验证了该算法的有效性。
針對除塵、脫硫、脫硝改造後火電廠負荷優化分配問題,從提高全廠綜閤經濟效益的角度齣髮,提齣瞭一種攷慮環境成本的全廠負荷優化分配模型和滿足電網調度實時性要求的可控搜索粒子群優化(PSO-CE)算法。基于機組實際運行數據,構建瞭供電煤耗和多種汙染物排放濃度特性模型,根據除塵、脫硫、脫硝補償電價和排汙費用標準,建立瞭麵嚮最優綜閤經濟效益的負荷優化分配模型和自適應負荷約束條件。在標準粒子群優化算法中引入可控隨機搜索的速度因子和動態調整的最大速度限製因子,使其具有平衡算法的計算耗時和尋優能力,併通過某火電廠4檯機組的負荷分配倣真試驗驗證瞭該算法的有效性。
침대제진、탈류、탈초개조후화전엄부하우화분배문제,종제고전엄종합경제효익적각도출발,제출료일충고필배경성본적전엄부하우화분배모형화만족전망조도실시성요구적가공수색입자군우화(PSO-CE)산법。기우궤조실제운행수거,구건료공전매모화다충오염물배방농도특성모형,근거제진、탈류、탈초보상전개화배오비용표준,건립료면향최우종합경제효익적부하우화분배모형화자괄응부하약속조건。재표준입자군우화산법중인입가공수궤수색적속도인자화동태조정적최대속도한제인자,사기구유평형산법적계산모시화심우능력,병통과모화전엄4태궤조적부하분배방진시험험증료해산법적유효성。
Against the load optimal distribution problems in power plants after dedusting,desulfurization, and denitrification,a whole plant load distribution model considering environmental cost and a controllable exploration particle swarm optimization (PSO-CE)algorithm satisfying the real-time request of power dis-patching were proposed,from the aspect of improving the plant comprehensive economic benefit.The net coal consumption characteristic model and the multiple contaminants emission concentration characteristic model were constructed on the basis of the unit actual operating data.Then,the load distribution model for optimal comprehensive economic benefit and the self-adaptive load constraint condition were established, based on the dedusting,desulfurization,and denitrification compensation electricity price and the standard expense of pollutants emission.Moreover,the velocity factor of controllable random exploration and maxi-mum velocity limiting factor of dynamic adj ustment were introduced to the standard particle swarm optimi-zation algorithm to balance the computing cost and search ability.Simulations on the load distribution of a power plant with 4 units reveal the validity of the proposed method.