Abstract
Aiming to improve the operation economy and power quality of distribution systems subject to the fluctuating and stochastic power outputs of distributed generation (DG) units and electric vehicles (EVs), a multiobjective optimization model for network reconfiguration and its corresponding solution method are proposed. First, a dynamic reconfiguration model is constructed based on the power loss rate (PLR) as well as the active power loss, the load balancing index and the maximum node voltage deviation, which serve as the optimization indexes. Second, the Levy flight and chaos disturbed beetle antennae search (LDBAS) algorithm is presented based on the grey target decision-making technique, which can not only improve the computational efficiency but also find the most satisfactory solution for the proposed dynamic reconfiguration model. Considering the uncertainties of loads and DG outputs, the influence on the load curve of EV connecting to the distribution network at different penetration rates and under different charging/discharging modes is analysed. Additionally, the modified IEEE 33-bus and 118-bus test radial distribution networks are simulated to verify the effectiveness and superiority of the presented reconfiguration model and the improved LDBAS method, and the results illustrate that the proposed reconfiguration method can improve the operation economy and power quality of the distribution system and encourage the penetration of EVs.
Highlights
With the advent of the green grid concept, the high-level penetration of distributed generation (DG) and electric vehicle (EV) charging loads is introducing new problems affecting the dispatching operations of distribution networks
In terms of the overall voltage profiles, we can clearly see that the voltage of the distribution network with EVs under the random charging pattern is decreased compared to scenario 1 without EVs, and the voltage drop becomes more severe as the penetration of EVs increases
The proposed reconfiguration model is validated on the modified IEEE 118-bus system with EV penetration rates of 0.25 and 0.5 by using the proposed LDBAS algorithm to solve the model
Summary
With the advent of the green grid concept, the high-level penetration of distributed generation (DG) and electric vehicle (EV) charging loads is introducing new problems affecting the dispatching operations of distribution networks. In 2014, a non-dominated sorting particle swarm optimization (PSO) algorithm was proposed to find the best solution for distribution network reconfiguration, considering solar and wind generation as well as three objective functions of a maximum power loss, a maximum voltage deviation and a maximum number of switching operations [25]. In [30]-[32], a hybrid evolutionary algorithm for obtaining the best combination of on/off statuses of the switches was introduced for a distribution network considering DG from various aspects, such as time-varying electricity prices and different load levels as well as demand response services with objective functions of operation cost and power loss.
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