Economic Power and Heat Dispatch in Cogeneration Energy Systems Using Manta Ray Foraging Optimizer

Abdullah M Shaheen,Ahmed Rabie Ginidi,Sherif S M Ghoneim,Ragab A El-Sehiemy

doi:10.1109/access.2020.3038740

Abstract

Economic Power and Heat Dispatch (EPHD) in Cogeneration Energy Systems (CES) is considered as one of non linear hard optimization problems. It is optimally scheduling the of heat and power generation units. It aims at minimizing the total fuel cost (TFC) of cogeneration units considering their operational limits. In this paper, a Manta Ray Foraging Optimization Algorithm (MRFOA), which is a recent meta-heuristic optimization technique, is developed to solve the EPHD problem in CES with additional non-convex valve point effects. The simplicity and effectiveness motivate the attempt of employing the MRFOA to minimize the TFC for power units only, cogeneration units and heat units only. The equality constraints by supplying the total loading of power and heat is are maintained. In addition, the inequality operational bounds of power only and heat only units are satisfied while the dynamic operational bounds of cogeneration units are not jeopardized. Three test systems are analyzed to estimate the MRFOA performance for solving the EPHD problem in CES, which involve 5 units, 7 units, and 48 units. It is worth noticing that the optimal solutions demonstrate MRFOA capability, feasibility and efficiency of better solutions obtained in terms of TFC compared with other optimization methods and the ability of implementation of MRFOA on EPHD issue in CES..

Highlights

Energy systems are pivotal basis for the survival and the development of national economy
There are some other swarm intelligent algorithms that has been integrated to the Economic Power and Heat Dispatch (EPHD) problems in Cogeneration Energy Systems (CES) such as bee colony optimization [31], artificial immune system algorithm [32], line-up competition algorithm [33], oppositional teaching learning based optimization algorithm (OTLBO) [34], multiplayer harmony search (MPHS) [35], quantum optimization (QO) [36], modified GSO (MGSO) [37] approach, and gravitational search algorithm (GSA) [38]
This paper has been developed for handling the EPHD optimization problem in CES

Summary

INTRODUCTION

Energy systems are pivotal basis for the survival and the development of national economy. There are some other swarm intelligent algorithms that has been integrated to the EPHD problems in CES such as bee colony optimization [31], artificial immune system algorithm [32], line-up competition algorithm [33], oppositional teaching learning based optimization algorithm (OTLBO) [34], multiplayer harmony search (MPHS) [35], quantum optimization (QO) [36], modified GSO (MGSO) [37] approach, and gravitational search algorithm (GSA) [38] These techniques utilized definite procedures on the basis of randomness to explore the space of feasible solution instead of the differential rules in the mathematical models. In the current paper, the MRFOA was employed to solve the EPHD problem in CES considering the valve-point loading effects and the operational constraints such as equality and inequality limits.

PROBLEM FORMULATION

MANTA RAY FORAGING ALGORITHM FOR OPTIMIZED EPHD IN CES

SIMULATION RESULTS

CONCLUSION