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
In support of the European Union's (EU) energy polices to increase the production of bioenergy, the production and use of Solid Recovered Fuels (SRF) were researched within the European Union's 6 and 7 research and development framework programs. It was shown that the use of SRF, which are produced from non-hazardous wastes, are a viable option to reduce fossil CO emissions, protect natural resources, recover energy from low polluting wastes, reduce landfill 2 disposal, stimulate regional economies, etc. Thus, the use of high quality SRF, e.g., in cement kilns and Combined Heat and Power (CHP) plants, working according to the EU Waste Incineration Directive (WID), is considered a tool for a resilient solid waste management strategy in smart cities of the future. This could also include urban planning that has an infrastructure for use of SRF in waste-to-energy plants or in waste-to-cement plants. A quality management system in accordance with RAL-GZ 724 guarantees reliable and high qualities of the produced fuel. Adding online analysis technology multiplies available analytical information and helps to improve SRF-quality additionally. Thus, combustion of SRF in CHP-plants or co-processing of a high quality SRF in cement kilns in combination with recycling of valuable materials like Fe-/NF metals should be a viable concept to implement for any smart city, regardless of the population size and location, with slight modifications to suit local conditions.
This paper proposes a Daubechies-10 Wavelet Transform (Db-10 WT)-based fault recognition technique for Wind Farm Integrated Series Capacitor Compensated Three Phase Transmission Line (WFISCCTPTL). Though many techniques have been reported for shunt fault detection, the detection of converting faults, near-in relay faults, far-end relay faults, multiposition faults, faults around series capacitor bank, and varying the wind turbine units in WFISCCTPTL have not yet been reported. The proposed Db-10WT-based technique detects faults by using the fault currents recorded only at single end. The single sided captured fault currents of WFISCCTPTL are then decomposed using Db-10WT. Further, the Db-10 WT evaluates the amplitudes of detail coefficients. The fault factors such as fault location, resistance, and switching time of WFISCCTPTL are varied. It has been investigated that Db-10 WT can detect every type of faults very well. It has been discovered that Db-10 WT is robust to the variation in fault factors of WFISCCTPTL.
Microgrids have become very popular over the past decades due to increase in use of distributed energy sources. Microgrids can be very useful to provide power in rural areas. The power switch to control across the hybrid microgrid is a vital aspect to pick up benefits. There are various techniques anticipated to control the power flow; however, majority of these techniques make use of proportional integral controllers, but due to its drawback of slow response and difficulty to tune, several innovative methods have been developed, which eliminate the drawbacks of existing control solutions. One of them is the hill climbing power flow algorithm, which uses perturbations of the power angle and observation of change in active power. Yet, this method is applied in a simple system; thus to check its feasibility and synchronism with other controllers, a complex hybrid microgrid model is proposed. In this paper, a generalized model of hybrid microgrid, consist AC microgrid, DC microgrid and main grid, presented, which including hill climb power flow control algorithm to manage power sharing between AC and DC microgrids, and a generalized MATLAB function has been generated to manage power flow from main grid. Simulation results are presented with different loading conditions. The model is implemented and tested in MATLAB/Simulink®.
Due to complex behaviour of power system networks, now-a-days systems are used in an interconnected rather than isolated form. In this paper, stability enhancement of SMIB (Single Machine Infinite Bus) is evaluated. The MATLAB is used as a simulink tool to examine the response of the system. The three main elements considered for the analysis of SMIB system are Synchronous Machine, Excitation System, and Power System Stabilizer (PSS). There are many control devices which are designed to minimize the low frequency oscillations, among them PSS is one of the effective control devices used frequently, which minimizes the oscillations of the system and maintains the stability. For performing the stability criteria, optimization technique is used. Harmony search optimization is preferred over Ant colony optimization and Genetic algorithm due to its fast rate of convergence.
In order to address the double-pronged challenge of energy security and climate change, it is important for India to tap into its renewable energy resources to replace fossil fuel generated energy that adversely impacts the environment, in terms of resource use and GHG , particularly CO emissions. Technologies that harness this renewable energy need to be 2 deployed at the points of consumption. Pune city in the heart of the state of Maharashtra faces rapid urbanization and a burgeoning demand for electricity. In fact, where energy consumption is concerned, the residential sector is the dominant sector amongst all others, consuming 40% of the total utility's supply. Of particular interest are high rise residential towers, which are expected to dominate the city's urban landscape in the near future. These account for a large energy demand, given the high density of tenements housed in a comparatively small building footprint. It is possible to supplement the energy consumption of these high rise residential buildings using renewable energy. With a low foot-fall, free space and good exposure to the sunlight, rooftops of these high rise residential buildings have potential for installing renewable energy systems like Solar Photo-Voltaics (SPV). This study aims to determine the rooftop SPV potential for a typical high rise residential building - 12 to 15 storeys with apartments for middle income group residents. Two complexes in Pune with 5 to 6 such buildings were studied for their electricity consumption and the potential of their rooftops to generate electricity from SPV systems towards meeting this consumption. Percentage of total energy demand of the apartment which can be supplemented with renewable energy was estimated. Payback calculations were done to assess the viability of capital investment in the RTPV systems. It was found that rooftops can meet 100% of the common electricity demand and generate revenue with a low payback period of 4 years.