Abstract
OAPD is basically a Generation Scheduling (GS) problem which is commonly formulated as an Optimal Power Flow (OPF) problem. OPF is a power system optimization tool which aims to optimize certain objective and provide the optimal operating state of power system simultaneously satisfying both physical and operational constraints of power system. The basic aim of OAPD problem is to determine the optimal GS for the committed generators in such a manner that the total fuel cost is optimized. The presence of nonlinear constraints like Valve-Point Loading (VPL), Prohibited Operating Zone (POZ), and Ramp Rate Limits (RRLs) makes the objective function nonlinear, non-convex, and sometimes discontinuous. This paper attempts to investigate the newly developed meta-heuristic algorithm called Exchange Market Algorithm (EMA) in solving highly nonlinear non-convex Optimal Active Power Dispatch (OAPD) problems of power system with VPL, POZ, and RRLs effect. Both continuous and discrete control variables are present in the problem which makes the optimization more complex. The problem is implemented on the standard IEEE-30 bus system. The results are compared with several other meta-heuristic algorithms, and it is found that EMA outperforms many contemporary algorithms in terms of the convergence rate and objective function value.
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Rajan, A., Malakar, T., Abhimanyu (2019). Solution of Constrained Optimal Active Power Dispatch Problems Using Exchange Market Algorithm. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 817. Springer, Singapore. https://doi.org/10.1007/978-981-13-1595-4_48
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DOI: https://doi.org/10.1007/978-981-13-1595-4_48
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