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
Globally, the supply of fossil fuels is rapidly depleting and the effects of their use on the climate are becoming more noticeable. Recent European initiatives and renewable targets have increased the awareness of carbon emissions and the need for increased use of renewable sources. The UK government is committed to meeting an ambitious target of producing 15 percent of the UK's energy demand from renewable sources by 2020. The aim of the study is to discover how arise in sustainable power generation for the UK domestic sector could be achieved. This is achieved by analysing the current UK electricity consumption within the domestic sector, identifying the current renewable generation methods used and attaining expert views on renewables and their future prospect. Two semi-structured interviews with experts in the field of renewable energy were conducted. It is clear that both believe that the future of renewable energy within the UK will primarily be in the form of wind and solar power however, technologies such as wave and tidal power were also discussed which also have the potential to play a role in the future of UK energy. Through analysing all the research, recommendations have been made for the future of renewables within the UK. It has been suggested that the UK government expands the use of renewables, with the majority of development in solar and wind; increased use of domestic renewable sources and alter consumer behaviour; and finally, a recommendation for the government to establish an initiative to encourage consumers to time-shift when they use electricity to enable the use of energy from intermittent sources when available.
This paper has been withdrawn by author.
In a competitive market environment, the provision of strategic bidding to the market participants and its consequences open up new challenging tasks to the system operator. The market economic efficiency is mainly dependent on transmission system support. The inability of transmission system support to drive market cleared schedule is known as congestion which is not desirable. At first stage, Differential Evolution (DE) technique is applied to optimize unconstrained market schedules for active power demand. In the second stage, Time-Varying Acceleration Coefficients-Particle Swarm Optimization (TVAC-PSO) algorithm is applied to minimize reactive power cost by optimizing the Unified Power Flow Controller (UPFC) parameters and voltage profile of the network simultaneously. Due to this approach, the congestion cost with redispatch and more reactive power cost payment to the market participants have been avoided. In addition to this, the system maximum loadability has been reduced. The analysis is carried out on IEEE 14-bus and IEEE 30-bus test systems and the results shown the validity of the proposed work in real-time.
This paper presents an intelligent approach to the improvement and optimization of control performance of a photovoltaic system with multi-stacked voltage equalizer based on fuzzy logic controller. A single-switch voltage equalizer using multistacked SEPIC is proposed to settle the partial shading issues to extract maximum energy from the Photovoltaic (PV) Systems. The single-switch topology can considerably simplicity of the circuitry compared with conventional equalizers, requiring multiple switches in proportion to a number of PV module/substring. The proposed voltage equalizer can be derived by stacking capacitor-inductor-diode (CLD) filter on SEPIC converter. Local MPPs were eliminated and extractable maximum power was increased by the equalizer. Fuzzy logic algorithms are simulated using a MATLAB fuzzy logic toolbox. An Adaptive Fuzzy Logic Control (AFLC) algorithm is employed to online regulate the equalization period, according to the voltage difference between panel voltage, not only greatly abbreviating the balancing time, but also effectively preventing over-equalization. A prototype with three PV panels is implemented to this paper. The equalization efficiency is higher than 98% equalization compared with the traditional analog control algorithm. This paper explains the basic results of fuzzy logic algorithms and provides the better algorithm for maximum output voltage.
In this research work a meta-heuristic algorithm known as Firefly Algorithm (FA) is used for optimizing the control variables for simultaneously optimizing the transmission system's Real Power Loss (RPL) and Voltage Stability Limit (VSL). Mathematically, this problem can be expressed as nonlinear equality and inequality constrained optimization problem having an objective function with the integration of both RPL and VSL. Transformers taps, Unified Power Flow Controller (UPFC) location and its parameters like series injected voltage magnitude and phase angle of UPFC are incorporated in the form of control variables during the formulation of the problem. The effectiveness of the proposed algorithm has been verified on IEEE 14-bus system. Simulation outcomes received with this new FA algorithm have been compared with the Real Coded Genetic Algorithm (RCGA) for the single objective of minimization of RPL and multi-objective with respect to RPL minimization and VSL maximization. In this paper Interior Point Successive Linear Programming (IPSLP) technique is also considered for the single objective of RPL minimization to compare with the FA technique. The simulation results show the effectiveness and also the superiority of the FA with regard to optimizing both RPL and VSL.