Day-Ahead Hourly Operation Planning of Distribution Networks with Photovoltaic Generation Integrated by Smart Inverters via Mixed-Integer Volt/Var Optimization Problems.

The penetration of distributed photovoltaic generation in distribution networks has become a reality; however, it still imposes challenges to be overcome, such as the operation of these networks with minimal deviations in voltage magnitude profiles. Thus, this work proposes the day-ahead hourly operation planning of distribution networks aiming at minimizing the deviation in voltage magnitude profiles by means of optimal tap ratio adjustments of transformers at substations, optimal settings of remote switchable capacitor banks along primary feeders, and optimal active and reactive power injections from the distributed photovoltaic generation by smart inverters. In such Volt/Var Optimization (VVO) problem, discrete control variables associated with tap ratios of transformers and equivalent susceptances of switchable capacitor banks are handled by sinusoidal penalty functions that modify the original mixed-integer nonlinear programming problem into a nonlinear programming problem with only continuous decision variables. Results obtained for distribution networks with 69 and 135 nodes show that the proposed VVO model and its resolution methodology are effective and efficient in reducing the deviation in voltage magnitude profiles whilst also reducing the distribution network overall reactive power demand. Keywords—mixed-integer nonlinear programming, distributed photovoltaic generation, smart inverters, Volt/Var optimization.

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