Studies On Economic Emission Dispatch Considering Wind Power Based On Multi-objective Optimization

With the depletion of fossil energy and the increase of the environment pollution problem, development and utilization of clean and green wind energy to generate electricity has been an imperative trend. The large-scale integration of wind farms bring good economic benefits and environmental benefits to the society, however, the stochastic characteristics and fluctuation and non-schedulability of wind power makes the uncertainty characteristics of wind power output. As a result, the large-scale integration of wind farms will bring a lot of problems to economic dispatch and reliable operation of power systems. With the increase of wind power capacity and the environmental protection becoming more and more severe, the traditional economic dispatch model is no longer suitable. As a result, the economic emission dispatch (EED) method considering both economic benefits and environmental protection has gradually become a hot research field. EED is an optimization problem that pursues neither the absolute minimum cost of generation or the absolute minimum emission level, but the best compromising between them. Based on the above background, the economic emission dispatch considering wind power penetration has been investigated in this paper.Firstly, wind speed probability distribution function were derived based on Weibull distribution, then the probabilistic distribution model of wind speed was transformed to probabilistic analytical model of wind farm power output. On the basis of the wind power model, in order to quantify the uncertainty of wind power, a generating cost model of wind farm was derived based on incomplete Gamma function from the direct cost for generation, the scaled average cost of overestimation and underestimation, then integrated into the traditional economic dispatch model as a part of objective function. This paper presents a new and efficient economic emission dispatch model considering the cost of conventional thermal power, wind power with stochastic characteristics and the pollutant emission’s penalty to minimize fuel cost and the emission of pollutant. The effects of wind power on energy conservation are also investigated here.Secondly, a newly developed optimization technique called Gravitational Search Algorithm (GSA) has been applied. GSA is a new and efficient meta-heuristic method based on the Newton’s law of gravity and mass interactions. GSA has the sample rules and high speed of calculation. In GSA, the searcher agents are collection of masses which interact with each other using laws of gravity and motion of Newton. In order to overcome the shortcoming of the basic GSA that easily full into local optimum, an improved combined method called HPSO-GSA is presented to solve economic emission dispatch problem, which has combined the GSA and the particle swarm optimization(PSO). Compared to the basic GSA, HPSO-GSA is improved from mass interactions, elitist tactics and global memory ability of PSO. Through example analysis of Giewwank function, the acceleration of the convergence speed, the improved solution quality and the stronger global searching ability are achieved with HPSO-GSA approach.Finally, in order to validate the practicability of the multi-objective optimization economic emission dispatch model considering wind power and the HPSO-GSA, IEEE 30-bus system having six conventional thermal generators has been considered as test system in the MATLAB. Two extra wind turbines are also placed in the system. After placing the wind power sources, those buses have been considered as PV bus. Optimum fuel cost, optimum emission, best compromising fuel cost and emission, best compromising emission and fuel cost considering wind energy obtained by HPSO-GSA are compared with those of GSA. Simulation result demonstrate that the HPSO-GSA surpasses the other available techniques in terms of solution quality and diversity. And the scheme of multi-objective optimization dispatch of wind energy integrated power systems can be more comprehensive and reasonable, at the same time also can reduce the fuel cost and pollutant emission.