• Energy Research

The Unified Power Quality Conditioner plays an important role in the constrained delivery of electrical power from a source to an isolated pool of load or from a source to the grid. This article is presented new control approaches for both series and shunt inverter. The proposed control algorithm for series and shunt converters based on FLC and synchronous reference frame theory respectively. The proposed approach eliminates the total harmonic distortions (THD) efficiently, and mitigates sag and swell present in the linear and nonlinear loads.

Abstract This paper presents a space vector pulse width modulation (SVPWM) control for a three-phase five-level diode clamped multilevel inverter (DCMLI) for photovoltaic (PV) systems. SVPWM algorithm uses a simple mapping to generate gate signals for the inverter. The location of the reference vector and time are easily determined. The maximum power point tracking (MPPT) is capable of extracting maximum power from PV array connected to each DC link voltage level. The MPPT algorithm is solved by fuzzy logic controller. A digital design of a generator SVPWM using hardware description language (VHDL) is proposed and implemented on a field programmable gate array (FPGA). This is done to achieve high dynamic performance with low total harmonic distortion (THD). Simulation and experimental results are given to verify the implemented SVPWM control in terms of THD. The results are compared with conventional sinusoidal pulse width modulation (SPWM) in terms of lower THD is obtained. Finally, the implementation on a FPGA is tested in a laboratory with a real prototype using a three-level three-phase voltage source inverter. Experimental results are presented to verify the effectiveness and accuracy of the proposed system. This scheme can be easily extended to an n-level inverter for PV system.

Abstract With the increasing threat to environment and the fast depleting fossil fuel resources, hybrid power systems consisting of two or more renewable energy sources such as solar PV, wind, biomass, ocean thermal-with or without the back up of diesel generator have come to the forefront. These hybrid systems are normally integrated with battery banks for total reliability; such systems have brought about better quality of life in remote areas of developing economics. The remote areas in the state of Tamil Nadu in India possess excellent renewable energy sources. These areas fall under different climatic zones, are sparsely populated and are in the process of development. Though these areas are connected to the grid, Tamil Nadu grid is not stable; it is currently experiencing 40% short fall in generation. Thus grid power is available to these remote areas only for 10 h a day and even when available, there are voltage frequency problems. This paper analyses the economic feasibility of installing and operating hybrid systems in these areas. The areas are divided into different climatic zones and the hybrid system economy is analyzed for each climatic zone on the basis of NPC (net present cost), consumption of diesel and renewable fraction for all climate zones. The analysis indicates that the interior climatic zone – the area would be the optimum climatic zone to install HPS PV/diesel. The sensitivity analysis proves that the NPC of such a system can be reduced. It is suggested that due to high initial cost, government subsidy is necessary to adopt the system on a large scale. Such a profit will encourage development of renewable energy utilization and bring about rapid development of these remote areas.

This paper presents a unique combination of an interleaved soft switched boost converter (ISSBC) run by a set of two photovoltaic panel (PV) with a distributed MPPT, suitable to guarantee MPPT even under partial shadowed conditions, managed by an adaptive neuro fuzzy inference system trained by the training data derived from a particle swarm optimization (PSO–ANFIS) unit. The ISSBC is followed by a, single phase cascaded H bridge five-level inverter (CHI) driven by the individual DC outputs of the ISSBC, with selective harmonic elimination scheme to eliminate typically the seventh order harmonics. A comparison of different intelligent distributed maximum power point tracking (MPPT) algorithms for photovoltaic (PV) system under partial shadow conditions is carried out. The use of the ISSBC guarantees mitigation of ripple and it is meant to handle higher currents with minimal switching losses. Simulation was carried out in the Matlab Simulink environment and an experimental verification with a scaled down model validated the proposed scheme. It has been thus established, by both simulation and experimental verification, that the PSO–ANFIS model of distributed MPPT scheme of control outperforms other schemes of control for MPPT.

This article presents a covariance matrix adapted evolution strategy (CMAES) algorithm to solve dynamic economic dispatch (DED) problems. The DED is an extension of the conventional economic dispatch problem, in which optimal settings of generator units are determined with a predicted load demand over a period of time. In this article, the applicability and validity of the CMAES algorithm is demonstrated on three DED test systems with a sequential decomposition approach. The results obtained using the CMAES algorithm are compared with results obtained using the real-coded genetic algorithm, the Nelder–Mead simplex method, and other methods from the literature. To compare the performance of the various algorithms, statistical measures like best, mean, worst, standard deviation, and mean computation time over 20 independent runs are taken. The effect of population size on the performance of the CMAES algorithm is also investigated. The simulation experiments reveal that the CMAES algorithm performs better i...

Abstract In developing countries like India, very limited observatory stations are available to collect daily global solar radiation (GSR). This paper focuses to develop a common model for daily GSR estimation and standalone hybrid power system (HPS) design in view of six different climate locations in India. A new strategy is applied for finding the daily GSR model in Madurai location in Tamil Nadu, India. It is based on new parameter, which is named as 'approximate-bright sunshine duration' from the real-time measurement. The remaining six locations are estimated from the new model developed. In addition, to improve the accuracy of estimation, the developed linear one input variable model is further modified as two input variable model, based on the latitudes of six different climatic locations. The performances of developed one-input and two input models are analyzed using statistical indicators. The result shows that the developed two input variable model has provided excellent estimations for Madurai and also other six Indian climatic locations of latitudes ranging from 9°N to 13°N. This work also projects a detailed analysis of HPS design based on three meteorological data inputs to cover the residential energy demand. The NASA data, predicted ANFIS data (estimated data) and the measurement data are used in the analysis for the HPS feasibility and size optimization. The analysis shows that the hybrid configurations are same for all the locations, whereas PV and converter sizes are varied in the range of 47–52 kW and 23–27 kW, respectively.

This paper is aimed at exploring the performance of the various evolutionary algorithms on multi-area economic dispatch (MAED) problems. The evolutionary algorithms such as the Real-coded Genetic Algorithm (RGA), Particle Swarm Optimization (PSO), Differential Evolution (DE) and Covariance Matrix Adapted Evolution Strategy (CMAES) are considered. To determine the efficiency and effectiveness of various EAs, they are applied to three test systems; including 4, 10 and 120 unit power systems are considered. The optimal results obtained using various EAs are compared with Nelder–Mead simplex (NMS) method and other relevant methods reported in the literature. To compare the performances of various EAs, statistical measures like best, mean, worst, standard deviation and mean computation time over 20 independent runs are taken. The simulation experiments reveal that CMAES algorithm performs better in terms of solution quality and consistency. Karush–Kuhn–Tucker (KKT) conditions are applied to the solutions obtained using EAs to verify optimality. It is found that the obtained results are satisfying the KKT conditions and confirm the optimality. Also, the effectiveness of KKT error based stopping criterion is demonstrated.

In this paper, modified non-dominated sorting genetic algorithm-II (MNSGA-II)-based optimal damping control of unified power flow controller (UPFC) has been designed to enhance the damping of low frequency oscillations in power systems. The robust damping of UPFC controller design is formulated as a multi-objective optimisation problem, thereby minimising the integral squared error (ISE) of speed deviation and input control signal (u) under a wide range of operating conditions. The effectiveness of the proposed controller is confirmed through nonlinear time domain simulation and Eigen value analysis. The results are compared with NSGA-II and conventional method. Simulation result reveals that the obtained Pareto-front using MNSGA-II-based UPFC controllers are better and uniformly distributed due to the controlled elitism and dynamic crowding distance concepts. The proposed modulation index of shunt inverter (mE)-based damping controller is superior to the other damping controllers under different loading conditions and improves the stability of system.

In this paper, a high efficiency soft switched two channel interleaved buck converter scheme for charging a lead acid battery bank is presented. This scheme uses the incremental conductance (INC) maximum power point tracking (MPPT). An internal model control system (IMC) is used for controlling the charging of the battery in the constant current mode, constant voltage mode, and trickle mode depending upon the state of charge (SOC) of the battery. Various subsystems of simulation and the results are presented. The simulation results are validated experimentally by using a 125 W photovoltaic (PV) panel unit and a 36 A H lead acid battery. The real time experiment is performed under climatic conditions of Madurai which is a city located in Tamil Nadu, India. The result of the proposed system has been compared against the Perturb and observe MPPT scheme. The results of both simulation and the experiment reveal that the proposed soft switched, internal model controller incorporated INC scheme of MPPT offers more close tracking of the PV power and is more efficient.