Abstract
This paper presents the solving unit commitment (UC) problem using Modified Subgradient Method (MSG) method combined with Simulated Annealing (SA) algorithm. UC problem is one of the important power system engineering hard-solving problems. The Lagrangian relaxation (LR) based methods are commonly used to solve the UC problem. The main disadvantage of this group of methods is the difference between the dual and the primal solution which gives some significant problems on the quality of the feasible solution. In this paper, MSG method which does not require any convexity and differentiability assumptions is used for solving the UC problem. MSG method depending on the initial value reaches zero duality gap. SA algorithm is used in order to assign the appropriate initial value for MSG method. The major advantage of the proposed approach is that it guarantees the zero duality gap independently from the size of the problem. In order to show the advantages of this proposed approach, the four-unit Tuncbilek thermal plant and ten-unit thermal plant which is usually used in literature are chosen as test systems. Penalty function (PF) method is also used to compare with our proposed method in terms of total cost and UC schedule.
Highlights
UC is very important problem for power system engineering
This paper presents the solving unit commitment UC problem using Modified Subgradient Method MSG method combined with Simulated Annealing SA algorithm
The UC problem for four-unit Tuncbilek thermal plant is solved by using the MSG method combined with SA algorithm
Summary
UC is very important problem for power system engineering. The problem can be described as a nonlinear, mixed-integer, and nonconvex and is considered to be a nondeterministic polynomial-time hard NP-hard problem 1. One of the methods based on dual optimization technique, MSG method, which has the best performance in eliminating the duality gap in the literature, is used for solving the UC problem. The disadvantage of the MSG method is that the zero-duality gap value depends on the initial value of the upper dual value. In this proposal approach constructs the dual problem and solves it without any duality gap for large class of nonconvex constrained problems. This proposed approach is compared to PF method because the MSG method removes some of the problems occurred in this method.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
