This manuscript proposes an Internet of Things (IoT) platform for energy management (EM) in multi‐microgrid (MMG) system to enhance the power quality with hybrid method. The proposed method is the consolidation of opposition based crow search optimizer (OCSO) and radial basis functional neural network (RBFNN), hence it called RBFNOCS technique. The main aim of this manuscript is to optimally managing the power and resources of distribution system (DS) by constantly track the data from IoT‐based communication framework. In the proposed work, every devices of home is interfaced with data acquisition module (DAM) that is IoT object along unique IP address resultant in large mesh wireless network. Here, the IoT‐based communication framework is used for facilitating the development of a demand response (DR) energy management system (EMS) for distribution system. The transmitted data is processed by RBFNOCS technique. By utilizing the RBFNOCS method, the active with reactive power processing for optimal capacity unbalance compensation smart VSIs share the obtainable neutral current (NC). Likewise, the DS IoT framework enhances these networks flexibility and gives feasible use of obtainable resources. Moreover, the RBFNOCS method is responsible for satisfying the total supply with energy demand. The proposed model is activated in MATLAB/Simulink site and the performance is compared with existing models, namely improved artificial bee colony, squirrel search algorithm and gravitational search algorithm based artificial neural network (SOGSNN), GOAPSNN, fruit fly optimization, and FORDF technique. When compared with the existing methods, the efficiency of the RBFNOCS method is 93.4501%.

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In the recent trends the electrical grid is being interconnected with various types of non-conventional energy sources like solar, wind, etc. Some of the sources like wind turbine generators are vulnerable to grid side voltage sags and short circuits. This paper provides the new LVRT (Low Voltage Ride Through) solution for balanced and unbalanced grid faults in an electrical power system network. Till now "Sen" Transformer was used as a power flow controller. In this paper the Sen Transformer is used as a series voltage compensator under fault condition. The simulated model of the "Sen" Transformer during the balanced and unbalanced grid faults for maintaining the voltage stability of the system is presented so that the sensitive load will stay connected to the grid and the grid will not lose its synchronism during the fault and normal operation can be continued after the fault .The proposed solution is proven to be reliable and cost-effective when compared with the emerging technology of dynamic voltage restorer (DVR).

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Majority of the industrial electrical loads requires balanced three phase supply but in reality there is unbalanced supply due to single phase loads like railway tracks etc.increasing use of non linear loads in modern power distribution network there are some power quality issues like voltage sags and voltage swells, this distortion of the power supply effect the loads which are connected to power distribution network. In order to improve quality of the power, in this paper a Sen Transformer (ST) technique as been proposed to minimize unbalanced voltage sags and swells. The proposed technique mitigates both voltage sag and swell during balanced and unbalanced operating conditions. The proposed ST consists of a programmable tap controller to compensate ride through faults in power system network. The proposed work as been implemented using MATLAB/SIMULINK software. To validate the proposed work, simulation results are presented.