Abstract
This paper reports a solution to a relevant scientific task of determining the weight coefficients for an optimal system of automated control over the level of electric energy generation by renewable energy sources in a combined electric power system. It has been established that existing control systems of electric power generation by renewable sources, based on solving a problem on multicriteria optimization, do not take into consideration a change in the quantitative and qualitative composition of electric consumers over time.It has been proposed, in order to determine those weight coefficients that influence the resulting solution to the problem on multicriterial optimization, to employ a mathematical apparatus of fuzzy logic. This has made it possible, in contrast to existing systems, to better account for a time-dependent change in the quantitative and qualitative composition of electricity consumers. It has been shown that it is expedient to choose, as the input parameters for a fuzzy model, the values for a coefficient of consumer load and a coefficient of load importance that takes into consideration the sensitivity of electric consumers to voltage deviations.A database of rules for a fuzzy system of weight coefficients determination has been constructed, which includes 15 rules of fuzzy production. The Mamdani algorithm has been used as an algorithm of fuzzy logic derivation. To determine the input and output linguistic variables we have used triangular and trapezoidal membership functions. The output parameter was defuzzified by the method of determining the center of gravity (centroid method).We have performed computer simulation of the optimal system of an automated system of control over the level of electric energy generation by renewable energy sources using the designed fuzzy unit for determining weight coefficients. Analysis of the simulation results has shown that the devised system of automated control makes it possible to increase the level of electricity generation to a network, as compared to existing systems
Highlights
The current stage of world energy generation development demonstrates tendencies towards a significant increase in the deployment of electric energy generating installations with renewable energy sources (RES)
Analysis of existing automated control systems (ACS) at RES-based installations has revealed that almost all ACS execute control laws aimed at limiting the level of electricity generation to a network depending on the fixed value of the voltage setpoint
The findings from our research demonstrate that the use of a fuzzy model based on the Mamdani algorithm to determine weight coefficients k1, k2 improves the operational efficiency of ACS of electricity generation by RES within integrated electric energy system (IEES) by taking into consideration the impact of a time-dependent change in the quantitative and qualitative composition of electrical consumers
Summary
The current stage of world energy generation development demonstrates tendencies towards a significant increase in the deployment of electric energy generating installations with renewable energy sources (RES). Analysis of existing automated control systems (ACS) at RES-based installations has revealed that almost all ACS execute control laws aimed at limiting the level of electricity generation to a network depending on the fixed value of the voltage setpoint. The disadvantage of such an approach to automated control is a significant reduction in cash revenues from the sale of electricity under a “green” tariff.
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