Application of new trends to economic dispatch of power systems

The increasing demand for an optimal power flow (OPF) toolfor studying power systems has been on the increase since thefirst OPF paper was presented in the 60’s. There are variousexisting models for the OPF problem. Some models includeonly the real power subproblem or only the reactive powersubproblem. Such a decoupled model suffices in some cases butcan lead to suboptimal solutions or may even be infeasible.Another common difference between OPF models is in theobjective function. The objectives can be one of : minimizetransmission losses, minimize deviations from a specifiedoperating point, minimize the number of control variables thatare altered, or, minimize the operating cost . The models alsodiffer in how they handle inequality constraints. Modeling theinequality constraints using hard limits can lead touneconomical solutions. Minimizing the operating cost is themost commonly employed objective.The single objective function of generation cost can no longerbe considered alone due to the environmental concerns that arisefrom the emissions produced by fossil- fueled electrical powerplants with different types of fuel. Environmental Economicdispatch is a multi-objective problem with conflicting objectivesbecause reducing the emission means reducing the fuel and thisleads to not satisfying the required demand loads.This thesis proposed a method to solve this problem in twoseperatly stages, the first to find the optimal values for the fuelcost and the results are used as initial values to the second stageto find the optimal fuel emissions then repeat these steps untilereach the optimal results. Also there is another proposed methodwhere the cost function and the emission function are combinedto form the multi-objective function using the price penaltyfactors. The artificial networks are used to solve this problemand reach the optimal values of the fuel cost and fuel emissions.