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Dynamic economic emission load dispatch of hybrid power system using bio-inspired social spider algorithm

机译:基于生物启发式社会蜘蛛算法的混合动力系统动态经济排放负荷调度

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摘要

In the face of depletion of fossil fuel and alarming concern for environmental degradation, the future energy scenario of the world is expected to lead by non-conventional distributed energy resources such as solar and wind among others. Combined heat and power is another form of distributed energy resource which produces heat as well as electrical power in a single process with an efficiency of more than 80% and also reduces emission level significantly. In this paper, a bio-inspired meta heuristic algorithm Social Spider has been used to simultaneously optimize cost of production as well as emission level of a hybrid power system consisting of wind power plant, solar power plant, combined heat and power generators, heat only unit and conventional generators so as to supply the dynamic demands of power and heat satisfying all equality and inequality constraints. Result shows that this algorithm is capable of solving such non linear multi objective optimization problem of hybrid power system.
机译:面对化石燃料的枯竭和对环境恶化的担忧,人们预计,未来的能源形势将以太阳能和风能等非常规分布式能源为主导。热电联产是分布式能源的另一种形式,它在单个过程中产生热量和电能,效率超过80%,并且还显着降低了排放水平。在本文中,以生物启发式的元启发式算法Social Spider被用于同时优化生产成本以及混合发电系统的排放水平,该混合发电系统由风电厂,太阳能电厂,热电联产,仅热能组成机组和常规发电机,以提供满足所有平等和不平等约束的动力和热量的动态需求。结果表明,该算法能够解决混合动力系统的非线性多目标优化问题。

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