Ameliorated Heuristic Search Method for Coordinated Generation Scheduling in Multi Objective Framework

Abstract

The thesis briefly reviews previous research in optimal power dispatch and various optimization methodologies. An emended salp swarm algorithm ESSA is proposed to solve Multiobjective thermal generation scheduling, which is an extension of the salp swarm algorithm. Further, to solve the dynamic scheduling problem, an ameliorated salp swarm algorithm has been proposed, employing a forward approach. The bi-objective problem is converted into a scalar objective optimization problem by proposing incremental power and random power price penalty methods. newlineWorldwide, increased power demand and fuel price inflation require the search for neoteric power sources. Therefore, the dynamic mixed energy generation scheduling problem is modeled. To handle the uncertainties of the wind and solar, their total share is limited as per the spinning reserves maintained by thermal units. Unit commitment of solar and wind generating units using an optimistic one-point crossover solution methodology ensures that the total share from wind and solar does not exceed the prescribed power share. This work incorporates wind and solar power generating units in a Multiobjective framework to address the coordinated thermal-solar-wind generation scheduling CTSWGS problem and presents two novel strategies to tackle it. This work proposes an amalgamated salp swarm optimizer (ASSO) and an ameliorated artificial hummingbird algorithm - AAHA. ASSO comprises the amalgamation of the salp swarm algorithm with the simplex search method - SSM and AAHA, which is the union of the artificial hummingbird algorithm and SSM. newlineHydrothermal generation scheduling aims to fulfil load demand across the scheduling period utilizing the available water to its fullest extent. Hence, CTSWGS problem is extended to consider short-term, multi-chain, and cascaded hydro units. ESSA is applied to solve the coordinated thermal-wind-solar-hydro generation scheduling problem.