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Abstract: Voltage regulation is an important task in electrical engineering for controlling node voltages in a power network. A widely used solution for the problem of voltage regulation is based on adjusting the taps in under load tap changers (ULTCs) power transformers and, in some cases, turning on Flexible Alternating Current Transmission Systems (FACTS), synchronous machines or capacitor banks in the substations. Most papers found in the literature dealing with this problem aim to avoid voltage drops in radial networks, but few of them consider power losses or meshed networks. The aim of this paper is to present and evaluate the performance of several multi-objective algorithms, including hybrid approaches, in order to minimize both voltage deviation and power losses by operating ULTCs located in high voltage substations. In particular, a well-known multi-objective algorithm, PAES, is used for this purpose. PAES finds a set of solutions according to Pareto-optimization concepts. Furthermore, this algorithm is hybridized with simulated annealing and tabu search to improve the quality of the solutions. The implemented algorithms are evaluated using two test networks, and the numerical results are analyzed with two metrics often used in the multi-objective field. The results obtained demonstrate the good performance of these algorithms. [Copyright &y& Elsevier]

Abstract: In this paper, we propose an efficient simulation-based two-stage scheduling methodology by integrating vector ordinal optimization (VOO) and response surface methodology (RSM) to make a good scheduling policy for fab operation. The suggested method combines local and global rules into a single rule, with the objective of simultaneously optimizing multiple performance indices. Our approach consists of 2 stages: rule combination selection, and parameter optimization. In the first stage, we apply the VOO techniques to effectively selecting good rule combination. Results show that 1 orders of computation time reduction over traditional simulations can be achieved. In the second stage, we adopt RSM and desirability function to tune the parameters associated to scheduling algorithm. The proposed approach is validated by means of a comparison with other scheduling policies. The results show that the proposed scheduling method is effective. [Copyright &y& Elsevier]

Abstract: Based on the baseline PI control structure, the control parameters of non-linear ALSTOM gasifier benchmark problem are optimized. Firstly, taking all the input and output limits under three load conditions as constraints, the relative IAE indices at six scenarios are calculated and optimized by using multi-objective optimization algorithm NSGA-II. A set of non-dominated solutions are obtained which facilitate the further improvement on the performance under coal quality change. Then among those non-dominated solutions, the solution with best coal quality flexibility comes to the fore through a selection procedure. The simulation results show that the optimization and selection procedure presented in this paper improves the baseline PI control performance with better dynamic responses and coal quality flexibility. [Copyright &y& Elsevier]