Abstract
A stochastic fuzzy chance-constrained programming model with multi-objective optimization for coordinated control of power loss and voltage in distribution systems with renewable energy is presented by taking power output of DGs and charging-discharging power of EVs as random fuzzy variables and load power as random variables. Considering the fuzziness and randomness of active power output of distributed generation systems with wind and solar energy and charging power of electric vehicles, the key parameters of probability density function are determined by fitting incomplete data of uncertainties such as wind speed, sunlight intensity and charging power of electric vehicles. According to the principle of random fuzzy compatibility, the probability density function of the uncertainties is transformed into the probability distribution function of the uncertainties. The NDC(Normal Distribution Crossover)-based non-dominated sorting genetic algorithm is used to solve the optimization problem, and the Pareto solution set of the multi-objective optimization problem is obtained. The feasibility and applicability of the proposed model and algorithm are verified by simulating IEEE-33 and IEEE-118 distribution system.
Highlights
Reducing power loss and voltage deviation has always been an important task in a distribution system, and power loss and voltage management become more serious and urgent due toThe associate editor coordinating the review of this manuscript and approving it for publication was Bin Zhou .uncertainties in output power of distributed generation(DG) and the charging power of electric vehicle(EV).Traditional optimization methods for distribution systems consider more issues such as optimal location and capacity of distributed generation systems, reconfiguration of distribution systems and charging and discharging of electric vehicles
Some reconfiguration problem of distribution systems with DGs and EVs, distributed generation systems are taken as ‘‘negative’’ load, and the power loss is minimized by optimizing the output power of distributed generation systems, but the problem of voltage deviation is not solved [3]
Considering the fuzziness and randomness of active power output from distributed generation systems and charging power of electric vehicles, a stochastic fuzzy chance-constrained programming model for coordinated control of power loss and voltage in distribution systems with DGs and EVs is constructed in this paper, and a multiobjective optimization method for coordinated control of power loss and voltage in distribution systems with DGs and EVs under renewable energy environment is proposed
Summary
Reducing power loss and voltage deviation has always been an important task in a distribution system, and power loss and voltage management become more serious and urgent due to. Considering the uncertainties in wind speed and load, a multi-objective reactive power optimization model of distribution systems with DGs and EVs is established [6]. Energy management in distribution systems with DGs and EVs is a optimization problem, which must be solved for optimally coordinating control of voltage and power loss [25]. Considering the fuzziness and randomness of active power output from distributed generation systems and charging power of electric vehicles, a stochastic fuzzy chance-constrained programming model for coordinated control of power loss and voltage in distribution systems with DGs and EVs is constructed in this paper, and a multiobjective optimization method for coordinated control of power loss and voltage in distribution systems with DGs and EVs under renewable energy environment is proposed. The rationality and superiority of the model and algorithm are analyzed by comparing the schemes, which is helpful to the collaborative control of power loss and voltage in distribution systems with DGs and EVs
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