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Optimization of Active Power Losses in Smart Grids Using Photovoltaic Power Plants

doi: 10.3390/en15030739
Optimization of Active Power Losses in Smart Grids Using Photovoltaic Power Plants
This article addresses the reduction of power losses in smart grids. Two optimization algorithms are used in this article. The first method is the enumerative method. The second method of the optimization calculation is based on the self-organizing migrating algorithm. In the first step, the network parameters are calculated based on the input data, and then the target function is determined. In this article, the target function is used to reduce the active power losses that occur during the operation of an electric network. More specifically, we attempt to determine the reactive power with the enumerative and SOMA algorithms to reduce the value of the active power losses. This article intends to illustrate the differences between the selected optimization algorithms. As observed, the optimization algorithm determines the computation time.
- Rzeszów University of Technology Poland
- Technical University of Košice Slovakia
- Technical University of Košice Slovakia
- Rzeszów University of Technology Poland
Technology, T, enumerative method, active power losses, smart grids, active power losses; enumerative method; renewable energy sources; self-organizing migrating algorithm; smart grids, renewable energy sources, self-organizing migrating algorithm
Technology, T, enumerative method, active power losses, smart grids, active power losses; enumerative method; renewable energy sources; self-organizing migrating algorithm; smart grids, renewable energy sources, self-organizing migrating algorithm
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).3 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
