A semi-definite programming (SDP) formulation of the multi-objective economic-emission dispatch problem is presented. The fuel cost and emission functions are represented by high order polynomial functions and this was shown to be a more accurate representation of the economic-emission dispatch (EED) problem. Furthermore, the polynomial functions of both objective functions are aggregated into a single objective function using the weighted sum approach. This thus reduces the problem to a standard polynomial optimization problem which was formulated as a hierarchy of semi-definite relaxation problems. The resulting SDP problem was then solved at different degrees of approximation. The performance of the proposed approach was evaluated by conducting experiments on the standard 6-unit and the 13-unit IEEE test systems. The results obtained were compared with those reported in the literature and indicated that SDP has inherently good convergence property and provides better exploration of the Pareto front.
This paper presents a method for managing congestion constraints in a hydro-thermal optimal power flow solution procedure. The congestion constraint is handled in this paper as an active power generation constraint. To achieve this solution, a power flow tracing technique is used to detect the generators contributing to line congestion to penalize them by reducing their outputs. The congestion is then removed by setting the maximum power of the affected generators to the penalized value. The proposed algorithm is implemented using MATLAB software. Finally, the performance of the proposed algorithm is tested and the results for the 5-bus, 30-bus, and 34-bus Nigerian power networks are presented.
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