International Journal of Applied Power Engineering (IJAPE)
Not a member yet
508 research outputs found
Sort by
AHP based technical, economic and environmental impact analysis with optimal DG placement in radial distribution network
Get PDFThis manuscript considers multi-criteria based multi-objective approach with technical, economic and environmental indices (TEE) for optimal placement and sizing of distributed generation (DG) units in the distribution network. Technical criteria include indices of active energy losses, voltage deviation; whereas economic criteria include the index of cost of DG installation, and environmental index considers the various greenhouse gas (GHG) emissions from generating unit’s and biomass DG. Combined sensitivity analysis is applied for sorting the candidate nodes for DG placement and reducing the search space. Multi-criteria decision-making among TEE factors are addressed using a scientific approach named Analytic Hierarchy process (AHP) approach. The impact of prioritized solutions is analyzed in terms of three scenarios formed using AHP in the form of TEE criterion. The developed formulation is tested on IEEE 33-bus bus radial distribution system and is solved using hybrid optimization approach (hybrid GA-PSO) and AHP based scenarios performed better than base case scenario (non-prioritized scenario)
A novel hybrid-fuzzy logic based UVC technique for solar-PV/grid integrated water-pumping system
Get PDFThe continual depletion of fossil fuels and increased green-house emissions are persuading the consumers to install micro-renewable energy sources-based water pumping system. Among numerous energy sources, the solar-PV plays a significant role in water pumping application due to its virtuous, environment friendly, noise-free and abundant nature, so on. Along with solar-PV, the grid integrated system enables the continuous operation of water pumping system during varying temperature and irradiance conditions, and also delivers available solar-PV energy to grid during non-functional of pumping system. The above operations are carried by using bidirectional inverter which is controlled by using unit-vector control (UVC) technique. It consists of proportional-integral controller, which is not suited for regulation of DC-link voltage at desired level because of improper selection of gain values. In this work, an intelligent hybrid-fuzzy logic based UVC technique evidences the intelligent knowledge base for better regulation of DC-link voltage and power-flow of bidirectional inverter. The performance and operation of proposed hybrid-fuzzy logic control UVC technique for solar-PV/Grid integrated water-pumping system is evaluated under various operating cases by using MATLAB/Simulink tool; simulated results are conferred with superlative comparisons
Nine level switched capacitor inverter with level shifted pulse width modulation approach
Get PDFThis article proposes a nine-level switched capacitor inverter (NLSCI) with a minimum number of switches. In recent years, switching capacitor (SC) multilevel inverters (MLIs) have become one of the most common inverter topologies. These proposed nine level switched capacitor inverter (NLSCI) do not deserve any external control unit for capacitor control. Since, the charging and discharging of the capacitors are controlled by the on and off states of switches. Furthermore, by employing fewer switches and DC voltage sources, the suggested design produces a greater amount of resultant voltage. Additionally, pulse width modulation (PWM) is recommended as a method to enhance output quality and power level quality. The switched-capacitor two-output multilevel inverter (SCMLI) structure's viability and effectiveness have been demonstrated using MATLAB simulation
Time-series trendline and curve-fitting-based approach to short-term electricity demand forecasting
Get PDFElectricity load demand forecasting and its accuracy is an important process for utility planning, maintenance, scheduling, operation, and control in power systems. Historical data are also very vital in demand forecasting processes. This study examined weekly electricity demand forecasting model using trendline methods which include linear trendline, moving average, exponential smoothing, quadratic, and logarithmic trends. The calculations and analysis were carried out using Microsoft Excel. The results were compared using known performance evaluation metrics such as mean absolute percentage error (MAPE) and root mean square error (RMSE). Cubic root mean error (CRME) was introduced as a performance evaluation metric. The hybrid (quadratic-logarithmic) method was found to outperform the other individual trendline methods. This method produced the lowest value of MAPE, RMSE, and CRME representing 14.41%, 14.68%, and 14.65% respectively which indicated that hybrid model performs better than individual models operating separately when used in forecasting
Lion swarm optimization for grid connected PV system with improved SEPIC
Get PDFThe wide deployment of grid-connected renewable energy system has piqued immense attention recently, in response to rising electricity consumption, diminishing fossil fuel reserves in addition to the need for reducing carbon emissions. Among the available sources of renewable energy, photovoltaic (PV) power generation is the most promising technology with enormous potential and easy access. This paper presents an optimum control technique for grid connected PV systems. The improved single ended primary inductor converter (SEPIC) controls and regulates PV output power to the optimum voltage level. The working of the improved SEPIC is controlled by a proportional-integral (PI) controller optimized by meta-heuristic technique of lion swarm optimization (LSO). The constant output from the converter is then supplied to the power grid through a single-phase voltage source inverter (1 VSI). The effectiveness of the proposed control strategy is ascertained using hardware validation with DSPIC3050FPGA controller and MATLAB simulation generating a reduced total harmonic distortion (THD) of 3.9% and 2.9%, respectively. Furthermore, the proposed system generates an enhanced voltage gain of 1:10 and an efficiency of 96%
A review of application of artificial intelligence for space vector pulse width modulated inverter-based grid interfaced photovoltaic system
Get PDFArtificial intelligence (AI) is being proposed for a range of subfields that deal with photovoltaic (PV) systems as a result of improvements in computer power, tool accessibility, and data generation. The methods employed at present in the PV industry for a variety of tasks, including the outcomes of design, forecasting, control, and maintenance, have been found to be relatively inaccurate. Additionally, the use of AI to carry out these tasks has improved in terms of accuracy and precision, which has made the topic itself highly interesting. In light of this, the goal of this article is to examine the effect AI approaches have on the solar value chain. The article involves creating a map of all currently accessible AI technologies, identifying potential future uses for AI, and weighing the advantages and disadvantages of these technologies’ relative to more conventional approaches. This article lays special emphasis on discussing AI techniques for improving the power quality in grid systems involving space vector pulse width modulated inverters interfacing the photovoltaic to the grid along with power converter defect monitoring, filter flaw detection, and battery monitoring
A novel PWM technique for reduced switch count multilevel inverter in renewable power applications
Get PDFThis paper described a novel pulse width modulation (PWM) technique in reduced switch count multilevel inverter (MLI) for renewable power applications. Therefore, the proposed technique finds a better solution in the multilevel inverters used for improving power quality, efficiency and reduction of switching and conduction losses. It produces a smoother sinusoidal output waveform with reduced total harmonic distortion (THD) using different modulation technique. The novel PWM technique consists of nearest level control (NLC) and level shift pulse width modulation (LSPWM). Normally semiconducting devices are added for increasing number of levels. It affects the power quality and efficiency due to losses. In this work, MLI topology with reduced number of switches count for NLC and LSPWM is presented. The single-phase and three-phase inverter configuration is used in proposed mythology. Detailed simulation results for 7-level inverter of single and three-phase inverters are presented in this paper. It is observed that NLC method is better efficiency and reduced THD than LSPWM for better utilization in renewable power applications
Improving fault identification in smart transmission line using machine learning technique
Get PDFIn this work inevitable for power transmission boards such as Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) to look for a low-cost communication system with low power usage and to improve supply reliability, to transmit reliable fault information back to the control centre in real time. This work aims to design an automated and effective fault identification and position system for all overhead power transmission network networks using all current fault indicator technologies, machine learning methods, and commercially tested communication technology to easily and reliably pin a transmission system's flawed point parts. This will help to people avoid touching the electrical wire and prevent electrical shocks and current wastage as well. Smart transmission lines have played a decisive role in developing human protection and preventing current wastage. The transmission line is opened and the state of the line is evaluated, and the information goes to electrical board (EB) office. The system monitors the data by sending the alert message to the person responsible for the GPS location, either via SMS or BUZZER, or by displaying the alert message lives. Transmission line distribution is broad and most of them are spread around the geographical environment
Effect of supply voltage variations on single-phase capacitor clamped multilevel inverter fed induction motor drive
Get PDFThis article presents the effect of supply voltage variations on single-phase capacitor-clamped multilevel inverter-fed induction motor drives. This research is tailored at determining the best torque value and speed to attain a stable state under input voltage variation and minimum time response to realize low percentage harmonic distortions. The effect of constant power quality disturbance harms the performance and behavior of asynchronous motors based on harmonic contents and other energy source integrations. The multilevel inverter has shown good performance in motor drives. This paper deals with the effect of input voltage variations on a single-phase multilevel capacitor-clamped inverter for asynchronous induction motor drives. A five-level capacitor-clamped inverter with an in-phase disposition pulse width modulation technique is adopted. Four high-frequency triangular carrier signals are generated and compared with a reference sinusoidal signal. As a result of this approach, the inverter switches firing signals are generated. The open-loop model is designed and simulated utilizing MATLAB/Simulink and results based on different values of supply voltage are presented. The current and voltage total harmonic distortions (THDs) obtained are 4.97% and 4.46% respectively at the best operating voltage of 400 V and at maximum torque of 47 Nm
Comparative analysis of recent metaheuristic algorithms for maximum power point tracking of solar photovoltaic systems under partial shading conditions
Get PDFThe photovoltaic (PV) system comprises one or more solar panels, a converter/inverter, controllers, and other mechanical and electrical elements that utilize the generated electrical energy by the PV modules. The PV systems are ranged from small roofs or transportable units to massive electric utility plants. The maximum power point tracking (MPPT) controller has been used in PV systems to get the maximum power available. In addition, the MPPT controller is much essential for PV systems to protect the battery devices or direct loads from the power fluctuations received from solar PV panels. There are several MPPT control mechanisms available right now. The most common and commonly applied approaches under constant irradiance are perturb and observe (P&O) and incremental conductance (INC). But such methods show variations in the maximum power point. In this sense, this paper analyses and utilizes two recent metaheuristic algorithms called artificial rabbit optimization (ARO) and the most valuable player (MVP) algorithm for MPPT applications. The performance comparisons are made with the most preferred traditional algorithms, such as P&O and INC. Based on the result obtained, this study recommends that ARO perform better in standard testing conditions than all the other algorithms, but in partially shaded conditions, the MVP algorithm performs better in terms of efficiency and tracking speed