hybrid evolutionary algorithm

One of the most important objectives of smart distribution networks (SDNs) is to achieve a secure and reliable network. This can be realized by optimal operation in the presence of active power sources such as the distributed generations (DGs), reactive power sources such as switched capacitor bank (SCB), active loads such as the demand response program (DRP), and various network management strategies such as network reconfiguration In this paper, the planning and operation of the active and reactive sources in the smart distribution network (SDN) including reconfigurable capability and demand response programming (DRP) considering the voltage security is presented. Hence, the scheme to considering simultaneous modeling of the economic, operation and security of SDN is expressed as three-objective optimization problem, where objective functions minimize the annual costs of the sources planning and operation of network and sources, minimize the voltage deviation function, maximize the voltage security index, respectively. Problem constraints contain AC optimal power flow and network reconfiguration equations, operation and planning model of active and reactive sources, DRP formulation, and voltage security limit. In the following, the proposed multi-objective problem converts to single-objective formulation using Pareto optimization technique based on weighted functions summation method. Then, the hybrid solver of the Krill Herd Optimization (KHO) and Crow Search Algorithm (CSA) uses to achieve the reliable optimal solution including low standard deviation. Finally, the proposed scheme is implemented on the 69-bus radial SDN. Results show a low standard deviation of 0.94%, verifying its ability in achieving unique response conditions. Additionally, SCBs are generally placed at the feeder end buses to improve VDF and VSI while injecting reactive power equal to their maximum capacity into the SDN. DGs are also installed at either the beginning or end buses of the feeders to improve the Cost, VDF, and VSI functions. DRPs operate in charging (discharging) mode during off-peak (off-peak and middle-load) hours to enhance operating costs. Accordingly, the proposed strategy improves the economic, operation, and VSI indices by approximately 20%, 46%, and 11.5%, respectively. It can also reduce annual energy losses by 40% and maximum voltage drops by about 52% but will lead to a slight overvoltage in the SDN. The obtained numerical results confirm the capabilities of this scheme in the improving of the economic, operation and security situation of the SDN.

In this paper, the robust planning of the islanded hybrid system (IHS) to create an integrated system with wind turbine, photovoltaic, diesel generator, stationary (battery) and mobile (electric vehicles) storages is presented. The proposed scheme minimizes the planning cost (including construction, maintenance, and operation) of the mentioned sources and storages, and environmental pollution level. This problem is constrained to operation and planning model of the different sources and storages, and power balance constraint in IHS. The proposed scheme is formulated in the Pareto optimization framework based on method of the summation of weighted functions. Also, the bounded uncertainty-based robust optimization (BURO) is used to model the uncertainties of load, renewable power, and energy of mobile storage. Then, the hybrid evolutionary algorithm according to composition of Krill Herd Optimization (KHO) and Grey Wolf Optimization (GWO) algorithms obtains an optimal solution including low standard deviation in the final response. Finally, it is seen that the proposed scheme has a suitable capability in the planning of the proposed system according to economic and environmental viewpoints based on obtained numerical results.