How to Cite: Akkaş, Ö.P., Arıkan, Y., and Çam, E., (2018). Application of AHP Method for Solving The Unit Commitment Problem in A Day Ahead Market, Technological Applied Sciences (NWSATAS), 13(4): 310-317, DOI:10.12739/NWSA.2018.13.4.2A0160. Technological Applied Sciences Status : Original Study ISSN: 1308 7223 (NWSATAS) Received: November 2017 ID: 2018.13.4.2A0160 Accepted: October 2018 Özge Pınar Akkaş Yağmur Arıkan Ertuğrul Çam Kırıkkale University, Kırıkkale-Turkey pozge.arslan@gmail.com; yagmurarikan@gmail.com; ertugrul_cam@yahoo.com DOI http://dx.doi.org/10.12739/NWSA.2018.13.4.2A0160 ORCID ID 0000-0001-5704-4678 0000-0003-0947-2832 0000-0001-6491-9225 CORRESPONDING AUTHOR Özge Pınar Akkaş APPLICATION OF AHP METHOD FOR SOLVING THE UNIT COMMITMENT PROBLEM IN A DAY AHEAD MARKET ABSTRACT The aim of unit commitment problem in power systems has been converted from cost minimization to profit maximization with the liberalization of power markets. The generation companies (GENCOs) schedule the units to maximize their profit for the forecasted prices in day ahead market (DAM). The generation scheduling of generators in deregulated environment is called as Profit Based Unit Commitment (PBUC). In this paper, an application of Analytic Hierarchy Process (AHP) is proposed to solve PBUC problem. The method is applied to 3- units power system. The results are compared with the methods in the literature. As shown in the study, the proposed AHP method introduces its applicability and efficiency for solving the unit commitment problem in a day ahead market. Keywords: Price Based Unit Commitment, Analytic Hierarchy Process, Decision Making, Power Systems, Day ahead Market 1. INTRODUCTION In the traditional regulated energy industry, unit commitment aims to optimizing generation units to fulfill load demand with minimum cost. However, the countries worldwide have liberalized their electricity markets for increasing economic efficiencies and reliability of the system. There is a competition among generation companies (GENCOs) in the energy industry so the structure of the power system is altering. In the traditional unit commitment, the objective is to minimize the operation cost and it is commonly defined as cost-based unit commitment [1]. Now, the generators are scheduled to maximize profit of GENCOs contrary to regulated market. It has different objective and referred as price or profit-based unit commitment (PBUC) [1]. In PBUC, it is not necessary to satisfy power demand while committing the units. Independent System Operator (ISO) monitor the power system operation. The PBUC evaluates power and reserve that are offered in the day-ahead market to get the maximum profit [2]. There have been many solution techniques presented in the literature for solving PBUC problems. Some of them are Lagrange Relaxation-Differential Evolution [2], Binary fireworks algorithm [3], Particle Swarm Optimization (PSO) [4], Genetic Algorithm [5], hybrid Lagrangian Relaxation-Particle Swarm Optimization [6], Memetic Algorithm [7], Shuffled Frog Leaping Algorithm [8], Artificial Immune System [9], hybrid Binary Successive Approximation (BSA) and Civilized