Development of a Semi-definite Programming Weighted Sum Based Approach for Solving Stochastic Multi-objective Economic Dispatch Problems Incorporating CHP Units

Alli, Kolapo and Jubril, A.M and Kehinde, L.O (2017) Development of a Semi-definite Programming Weighted Sum Based Approach for Solving Stochastic Multi-objective Economic Dispatch Problems Incorporating CHP Units. IAENG International Journal of Computer Science,.

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Abstract

This paper has presented a weighted sum based semidefinite programming (SDP) optimization technique for solving stochastic multi-objective economic dispatch (MOED) model that incorporates Combined Heat and Power (CHP) units. The stochastic multi-objective model was transformed into its deterministic equivalent through their expectation, with the assumption that involved random variables are normally distributed. The multi-objective problem was recast in matrix form as a SDP relaxation problem and subsequently solved with a MATLAB programming suite. The system inequality and equality constraints uncertainty were entered into YALMIP, which is a linear matrix inequality parser. Simulations were performed on modified IEEE 6 and 20 units’ networks with 2 CHP units. The efficiency of the proposed method is deter- mined by investigating reformulated problems in stochastic and deterministic models on power dispatch. The standard weighted sum method is utilized in generating the Pareto-optimal solution between two objectives’ functions. An optimal selection of control weight selection k 1 parameter that provides a better convergence property and moderately good extent of the Pareto distributions was empirically determined. The proposed SDP method performed well in accuracy of results and providing lower operational cost in the Pareto set produced

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