Sanjay Kumar Sinha

The integration of renewable energy sources, particularly grid-tied solar photovoltaic (PV) systems, into the modern power grid has become increasingly prevalent. However, ensuring the reliable and efficient operation of grid-tied PV systems under various grid conditions, including fault scenarios, poses a significant challenge. In the event of grid faults or disturbances, traditional control methods often fall short in maintaining stable and reliable operation. This paper introduces a multi-layer neural network (MLNN) based MPPT controller that adapts intelligently to grid fault conditions, mitigating the impact on the grid-tied PV system's performance and providing low voltage ride through (LVRT). The research employs a detailed simulation framework on MATLAB to validate the effectiveness of the proposed controller under fault conditions. The LVRT capability of the designed system was analyzed and validated according to Indian grid code. The proposed controller leverages its capacity to learn and make real-time decisions to optimize the active and reactive power outputs of the PV system as per the grid code. Simulation results demonstrate that the proposed controller not only improves the fault tolerance of grid-tied PV systems but also enhances their performance, ensuring a stable and continuous power supply in the face of grid disturbances.

This work emanates from our personal conviction in renewable energy & its practical effect in the field. The real time data regarding power consumption to demonstrate the impact of solar energy technology is presented here. The improvement in efficiencies is gained due to installation of solar PV modules. The power consumption pattern before and after the installation of renewable energy technologies in Amity University Uttar Pradesh, Noida is compared quantitatively. The detail data regarding seasonal & monthly variations in power consumption is discussed. The paper provides future trends in renewable energy technologies deployment at Amity campus and chart the course towards sustainability and a pollution free world.

In large electrical power generation systems the integrated operation of hydro and thermal power stations is considered to be more economical as compared to thermal power generation. Integrated operation results in optimum utilization of all energy sources in the most economical manner, to provide an uninterrupted supply to the consumers. Through a case study present paper aims at optimizing traditional thermal plants along small hydro power plants, for fuel cost efficiency. The overall system is optimized using Genetic Algorithm such that the cost of running the thermal power plant is gradually decreased by supplying the demand through other renewable energy sources same.

Power flow study is the initial step which provides voltage magnitudes, phase angles, active and reactive power flows at respective buses under normal operating conditions. It helps in analyzing the current state of the power system and effective alternative options for expanding the existing system in order to meet with the increasing load demand. Contingency Analysis is also a major part of study for reliable and planned operation of power system. It is very significant function in modern Energy Management Systems. The objective of contingency analysis is to give operator the information about the static security. There are several factors which may lead to the contingency in power system, for example line outage, transformer outage, generator outage and overloads resulting the extreme situations such as voltage collapse, over loads in other branches and/or sudden system voltage rise or drop. Contingency analysis is used to calculate parameters violations. In this paper, maximum loading parameter is calculated and contingency status of Western System Coordinating Council 3 Machine, 9 Bus test system is done using PSAT toolbox in MATLAB.

This paper analyzes the importance of estimating the value of service reliability for electric utility customers. The electricity outage cost is estimated for residential and commercial category of customers in ten districts of a northern Indian state of Rajasthan as a case study. To obtain responses from the customers a survey questionnaire is framed containing issues related to quality of power supply, losses against outage, customer's desire to have an uninterrupted power supply, compensation for increased outages and choice of alternative action to avoid or nullify the effect of an outage. The outage cost is calculated by two approaches namely preparatory action approach and contingent value approach. Results of this study are meaningful from the utility's perspective in order to ensure the adequate service continuity and customer satisfaction.

In this work applications of Flexible AC Transmission System (FACTS) devices have been used in Automatic Generation Control (AGC) to improve the performance such as oscillation damping of transient response of power system in deregulated environment. The oscillations in frequency, tie power, generated power etc. are compared with conventional integral controller and FACTS devices. The responses improve further when Fuzzy controller is used in place of integral controller with FACTS devices connected to the system.

SUMMARY: An optimal controller has been designed for automatic generation control (AGC) of two‐area restructured power system. The performance of the controller has been studied for two cases: (a) when the tie line connecting the two areas consists of parallel EHVAC and HVDC lines and (b) when HVDC link is absent and only ac tie line acts as interconnection. The comparison has been done for the two cases in terms of time taken to damp out oscillations of frequency in each area, tie‐line power exchange between the two areas and power generated by each generator when there is change in load. The simulation results indicate that control performance improves when HVDC link is connected in parallel with EHVAC tie line and output of the dc block is considered as additional state for the optimal controller. Detailed simulation studies were carried out for load demand by DISCOs as per cotracted condition as well as for bilateral contract violation condition. Optimal controller gives better dynamic response compared to conventional PI controller. AGC dynamic response is further improved by using combined optimal fuzzy controller. Particle swarm optimization (PSO) technique has been used for tuning the fuzzy controller. The results of the two area thermal–thermal system indicate better control performance in terms of peak overshoot and settling time by PSO tuned combined optimal fuzzy controller as compared to the un‐tuned controller. Copyright © 2011 John Wiley & Sons, Ltd.