Inexactness of the Hydro-Thermal Coordination Semidefinite Relaxation

Hydro-thermal coordination is the problem of determining the optimal economic dispatch of hydro and thermal power plants over time. The physics of hydroelectricity generation is commonly simplified in the literature to account for its fundamentally nonlinear nature. Advances in convex relaxation theory have allowed the advent of Shor's semidefinite programming (SDP) relaxations of quadratic models of the problem. This paper shows how a recently published SDP relaxation is only exact if a very strict condition regarding turbine efficiency is observed, failing otherwise. It further proposes the use of a set of convex envelopes as a strategy to successfully obtain a stricter lower bound of the optimal solution. This strategy is combined with a standard iterative convex-concave procedure to recover a stationary point of the original non-convex problem.Comment: Submitted to IEEE PES General Meeting 201

Improved particle swarm optimization algorithm for multi-reservoir system operation

AbstractIn this paper, a hybrid improved particle swarm optimization (IPSO) algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimization (PSO) algorithm is improved in two ways: (1) The linearly decreasing inertia weight coefficient (LDIWC) is replaced by a self-adaptive exponential inertia weight coefficient (SEIWC), which could make the PSO algorithm more balanceable and more effective in both global and local searches. (2) The crossover and mutation idea inspired by the genetic algorithm (GA) is imported into the particle updating method to enhance the diversity of populations. The potential ability of IPSO in nonlinear numerical function optimization was first tested with three classical benchmark functions. Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants. The scheduling results of the IPSO algorithm were found to outperform PSO and to be comparable with the results of the dynamic programming successive approximation (DPSA) algorithm

Short-term generation scheduling in a hydrothermal power system.

SIGLEAvailable from British Library Document Supply Centre- DSC:D173872 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Hydropower Scheduling Toolchains:Comparing Experiences in Brazil, Norway,and USA and Implications for Synergistic Research

While hydropower scheduling is a well-defined problem, there are institutional differences that need to be identified to promoteconstructive and synergistic research. We study how established toolchains of computer models are organized to assist operational hydro-power scheduling in Brazil, Norway, and the United States’Colorado River System (CRS). These three systems have vast hydropowerresources, with numerous, geographically widespread, and complex reservoir systems. Although the underlying objective of hydropowerscheduling is essentially the same, the systems are operated in different market contexts and with different alternative uses of water, where thestakeholders’objectives clearly differ. This in turn leads to different approaches when it comes to the scope, organization, and use of modelsfor operational hydropower scheduling and the information flow between the models. We describe these hydropower scheduling toolchains,identify the similarities and differences, and shed light on the original ideas that motivated their creation. We then discuss the need to improveand extend the current toolchains and the opportunities to synergistic research that embrace those contextual differences.Hydropower Scheduling Toolchains:Comparing Experiences in Brazil, Norway,and USA and Implications for Synergistic ResearchacceptedVersio

Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms

In this paper, Cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIWPSO) and Social Ski-Driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS