Thermodynamic and Exergoeconomic Operation Optimization and Simulation of Steam Generation Solar Power Plant
Topology Transformation Approach for Optimal PMU Placement for Monitoring and Control of Power System
Performance Evaluation of Power System with HVDC Integration: Impact of SSSC and STATCOM on Power System Efficiency and Stability
Photovoltaic Systems: A Pollination-Based Optimization Approach for Critical Industrial Applications
Design of a Robust Controller for the Load Frequency Control of Interconnected Power System
Multi Area Load Frequency Control of a Hybrid Power System with Advanced Machine Learning Controller: Case Study of Andhra Pradesh
A New Hybrid Cuckoo Search-Artificial Bee Colony Approach for Optimal Placing of UPFC Considering Contingencies
Efficiency and Investment Comparison of Monocrystalline, Polycrystalline, and Thin Film Solar Panel Types at Karabuk Conditions
Design of a Grid Connected PV System and Effect of Various Parameters on Energy Generation
Comparative Analysis of Harmonics by Shunt Active Filter using Resonant Current Control in Distribution System
Optimal Distributed Generation Placement for Maximum Loss Reduction using Teaching Learning Based Optimization through Matlab GUI
Development of Power Flow Controller for Grid Connected Renewable Energy Sources Using Lyapunov function
Detection and Location of Faults in Three Phase 11kv Underground Power Cables By Discrete Wavelet Transform (DWT)
Design of PV-Wind Hybrid Micro-Grid System for Domestic Loading
Applications of Artificial Neural Networks in various areas of Power System; A Review
Thermoeconomic models, combining the concept of cost in economics and the concept of exergy in thermodynamics, provide the ability to optimize complex power generation systems to achieve the best balance between thermodynamic efficiency and economic cost. In this paper, a parametric analysis was carried out based on the method of calculating the unit exergy cost, as well as exergo-economic studies and cost sensitivity studies on the exergy of the cycle of a gas turbine power plant. The mathematical models of mass, energy, effort, and economy were created and presented. Thermodynamic properties and research analysis are performed using the MINI- REFerence fluid PROPerties (MINI-REFPROP) and matrix laboratory (MATLAB) SIMULINK software packages. The analysis leads to valuable benchmarks of the economic situation. The exergo-economic coefficient, the total cost of exergy loss, exergy destruction for the combustion chamber, and labor productivity are determined. When conducting parametric studies, the influence of the temperature at the inlet to the gas turbine, the temperature at the inlet to the air compressor, and the degree of pressure increase in the compressor were taken into account. The combustion chamber at the plant was found to have the highest energy destruction rate of 80%, indicating that boilers need to be given more attention in terms of design, selection, operation, and maintenance. However, in percentage terms, the combustion chamber has a high improvement potential of 94%. Sensitivity and parametric analysis show that while the exergy factor, the total cost of exergy loss, exergy destruction for the combustion chamber, and power output fall with increasing air compressor inlet temperature, it can be increased with increasing compressor pressure ratio. The total energy loss cost, combustor energy loss, and power output decrease as the gas turbine inlet temperature rises, while the cycle network and overall exergy destruction rate increase. The rates of the exergy destruction of the Venture Capital (VC), the combustion chamber of the combustion chamber, and the total exergy destruction are 25.2, 122.3, and 153.2 MW, respectively, for the proposed conditions. In addition, the results showed that it was $2,272 per hour, while the cost of work performed in energy terms is $1,769 per hour with a fuel cost of $0.003 per MJ. A valuable achievement is the availability of defined values and clear parametric influences, which can be of great help to engineers and site operators in the efficient execution of unique tasks, playing with the conflicts of energy use, exergy, and cost.
One of the major research topics in electrical engineering in recent years is load prediction. Short-term load forecasting is necessary for the design, operation, and management of the power system. It is used, among others, by utilities, system operators, electricity producers, and suppliers. Artificial Neural Networks (ANN) have been used for short-term load prediction. The work has been completed to ensure day-to-day operations. Here, the proposed neural networks were trained and tested using newly available data from Hubli Electricity Supply Company Limited (HESCOM). This paper presents a method for predicting the load of a power system based on a Neural Network (NN). Matrix Laboratory (MATLAB) software is used to create training and test simulations. The error was defined as Mean Absolute Percentage Error (MAPE).
A Multiple-Input Boost Converter (MIBC) with high boosting ability is suggested in this article. This converter can be utilized for solar photovoltaic applications. The converter is capable of driving continuous current from the sources. The converter's steady-state analysis is presented. The Maximum Power Point (MPP) tracking algorithm is applied for the absorption of peak power produced from the solar panels individually and simultaneously. The suggested converter can attain the voltage gain up to 20 times with maintaining continuity in the input current. The proposed MIBC's open-loop steady-state operation is validated in a simulation environment.
A dual-source voltage inverter system is proposed to improve the power and consistency aspects of using a microgrid. Evaluation of the Proportional Integral (PI), the intelligent Fuzzy Logic Controller (FLC), and the developed control method is known as the Instantaneous Symmetrical Component Theory (ISCT). A Dual Voltage Source Inverter (DVSI) uses Distributed Energy Resources (DER) to exchange power and compensate for unbalanced and non-linear loads in the system. The direct-quadrature-zero transformation (Dq0) conversion is used to obtain the positive sequence voltage. To evaluate the system control method, an inverter connected to a three-phase, four-wire distribution combination is used. The proposed system is verified by MATLAB simulation methods using a PI controller and an intelligent FLC system.
The steady rise in energy demand, combined with the loss of conventional resources, spurs research into environmentally benign renewable energy sources like solar and wind. These sources are appropriate for rural, urban, and offshore areas because to their ease of installation, low operating costs, and copious supply (sun light and wind). In the event of a problem, the distant locations are typically in the middle of nowhere, far away from technical support. This drives research towards fault-tolerant converter technology. These fault-tolerant converters improve reliability, ensuring that key loads receive uninterrupted power. This paper will discuss the redundant path approach, which is an essential part of controlling multilevel inverters under fault-conditions. Suggested fault diagnosing methods are also discussed in this paper. Computer simulation and lab results validate the proposed controls.
In the modern world, all industries are striving for rapid expansion through the introduction of various advanced technologies, including the agricultural sector. The aim of this paper is to design a solar-powered automatic seed sowing mechanism. The main goal of this design is to create a low-cost, solar-powered, seed- sowing device that can be easily used by farmers. This gadget uses a solar panel to absorb solar energy, which is then converted to electrical energy. The entire device can be fully powered by solar energy, eliminating the need for fossil fuels. In the sowing mechanism, seeds are supplied through two hoppers on either side of the machine. The seeds come out of hopper and are collected by a fan-shaped device that picks the seed from the feeder and places them on the other side of the U-shaped container. The seeds are subsequently released into the ground through a circular aperture. The drive shaft of the machine is connected to this apparatus, which simultaneously rotates both of them. The planted seed is covered is with the soil is covered by new earth applied to the seeds using a plate adjuster. The whole process is automated through a programmed microcontroller without human intervention.