Fuzzy reactive power optimization in hybrid power systems |
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Affiliation: | 1. EMD International A/S, Niels Jernes vej 10, 9220, Aalborg Ø, Denmark;2. Aalborg University, Rendsburggade 14, 9000, Aalborg, Denmark;1. Schneider Electric DMS NS, Novi Sad, Serbia;2. University of Novi Sad, Faculty of Technical Sciences, Department of Power, Electronic and Telecommunications, Novi Sad, Serbia;1. Department of Electrical Engineering, Chonnam National University, Gwangju 500-757, Republic of Korea;2. Institute of Electric Power IT, KEPCO KDN Co. Ltd, Seoul 137-862, Republic of Korea;3. Department of System Operation & Control, Korea Power Exchange, Seoul 135-791, Republic of Korea;1. LSS-SUPELEC, Gif-sur Yvette, France;2. Universidad de Sevilla, Camino de los descubrimientos, s/n. 41092 Sevilla, Spain;3. Boulevard François Mitterrand, 91000 Évry, France |
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Abstract: | Reactive power control, which is one of the important issues of power system studies, has encountered some intrinsic changes because of the presence of the hybrid AC/DC systems. The uncertainty in determination of some ill-defined variables and constraints underlines the application of fuzzy set as an uncertainty analysis tool. Herein a fuzzy objective function and some fuzzy constraints have been modeled for the purpose of reactive power optimization then this fuzzy model is dealt with as a linear programming problem to be solved. Contrary to the separate modeling of the conventional AC/DC optimization methods, this study attempts to attain the most optimal solution by the simultaneous employment of the total contributing factors of both AC and DC parts. In this way, the conventional issue of the coordinated control of firing angle and the transformer tap of the DC terminals is resolved, yet the method provides more flexibility to gain the most optimal condition since it uses more control factor for solving the optimization problem. The proposed method is performed on the modified IEEE 14 and 30-bus systems; and it is shown to have less computational burden and further minimized objective function than the conventional method. |
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