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Stochastic Economic Load Dispatch with Multiple Fuels using Improved Particle Swarm Optimization

机译:使用改进的粒子群算法的多种燃料随机经济负荷分配

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In this paper, Stochastic Economic Load Dispatch (ELD) problem with multiple fuels is solved using Improved Particle Swarm Optimization (IPSO). Generally, ELD problem is solved using deterministic models, but data required for such studies are rarely available with complete certainty. So uncertainties in unit’s generation, load demand and cost coefficients should be considered to get actual scenario. Thus, stochastic model for ELD problems is more suitable than deterministic model from the utilities point of view. ELD problem with deterministic model is first solved using IPSO to examine the effectiveness of the proposed method. Then IPSO is applied for ELD problem with stochastic model to investigate the real generation cost.
机译:在本文中,使用改进的粒子群优化算法(IPSO)解决了多种燃料的随机经济负荷分配(ELD)问题。通常,ELD问题可使用确定性模型解决,但此类研究所需的数据很少能完全确定。因此,应考虑机组发电量,负荷需求和成本系数的不确定性,以获取实际情况。因此,从效用角度来看,ELD问题的随机模型比确定性模型更合适。首先使用IPSO解决具有确定性模型的ELD问题,以检验该方法的有效性。然后采用随机模型将IPSO应用于ELD问题,以研究实际发电成本。

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