Short-term optimal hydrothermal scheduling with power flow constraint

Abstract

Short-term optimal hydrothermal scheduling(STOHS) problem [1] is usually supposed to find a reasonable scheduling scheme in a period of time(mostly 24h) while satisfying various constraints. The scheduling scheme aims to make full use of water resources, reduce the proportion of the thermal generation, minimize the operating cost of the hydrothermal system. Scholars have done many mathematical model researches about the hydrothermal power system since Ricard first put forward a mathematical model of optimal coordination of hydrothermal power system in 1940s. These researches mainly focus on the effect of head variation, electrical efficiency [2][3][4], value point of thermal generator [5] and the transmission loss of the active power [6] without consideration of the electricity network structure and effect of the reactive power. Power flow constraint is an important method to consider the effect of the electricity network and reactive power. The key point of the paper is to introduce the power flow constraint into the hydrothermal scheduling for the advantages to reflect the real working states of the hydrothermal power systems. The STOHS problem is a dynamic optimal power flow(OPF) problem essentially after taking the power flow constraint into account. There are only a few scholars who have added power flow constraint in the optimal hydrothermal scheduling model [7].Although Newton method and interior point method are usually used to solve the OPF problem [8-9] , both of the two methods have difficulties in solving the STOHS problem. One vital point of the difficulties is that the two methods are base on the condition that the objective function is derivable or differentiable. But the objective function about different This work was supported by National Natural Science Foundation of China (No. 61403321) and Knowledge Innovation Program of Shenzhen City (No. JCYJ20130327150859765).purpose of the hydrothermal scheduling is not always derivable and differentiable. As a member of the modern optimization algorithm, particle swarm optimization(PSO)[10] algorithm has no request about the derivability and differentiability of the objective function and it is more flexible and scalable, which gives PSO algorithm advantages to solve the STOHS problem. PSO algorithm has been developed a lot for its fast rate of convergence, simple principle and convenience to be programmed since it was put forward. An improved particle swarm optimization is applied to the STOHS problem in this study. The algorithm is verified by the IEEE nine buses test system, and the results show the feasibility and efficiency of the algorithm. This paper is organized as follows. Section 2 gives the formulation procedure of the STOHS problem. Section 3 takes an overview of the improved PSO algorithm. Section 4 shows the solving procedures of the improved PSO algorithm. Section 5 shows the simulation result of the IEEE nine buses test system. Finally, section 6 makes a conclusion of the paper. PROBLEM FORMULATIONSThe purpose of the STOHS is to make full...

A Novel Algorithm for Optimal Operation of Hydrothermal Power Systems under Considering the Constraints in Transmission Networks

“…For instance, the HTS problem was discussed in [1][2][3][4][5][6][7][8][9][10][11][12] and the OPF problem was presented in . However, combining the OPF and HTS problems was attempted by the authors in [48][49][50][51][52][53][54]; but they only use methods belonging to the deterministic algorithms [48][49][50][51][52][53] applied in the past three decades. In order to solve this combined problem, Newton's is the first method applied, where IEEE systems from 5 to 118 buses accompanied by a fixed-head short-term hydropower plant model are tested.…”

“…They have built and solved their own problem data and their applied method could handle the problem. On the contrary, in [53], the authors have proposed an improved particle swarm optimization (PSO) algorithm to solve the eight-bus system; as in previous studies, the improved PSO is used in order to obtain the optimal solution for the HTS problem while satisfying the constraints of the OPF problem. The authors of [54] have developed a conventional cuckoo search algorithm (CCSA) for solving the hydrothermal optimal power flow problem (HTOPF) and the performance of the conventional CSA was also compared via conventional PSO.…”