8 research outputs found
Optimal design, prefeasibility techno-economic and sensitivity analysis of off-grid hybrid renewable energy system
No full textThis work aims to find an optimal hybrid renewable system design using solar, wind energy, battery storage, thermal loads, thermal load controller (TLC), boiler, and a diesel generator (DG) for the considered site. The prefeasibility techno-economic analysis has been carried out using HOMER software to meet the load demand requirement of the village. For identifying winning system architecture, minimum net present cost (NPC), lowest cost of energy (COE), and the highest renewable fraction (RF) are used as the criteria. The obtained results show that the least cost-optimal hybrid system consists of 614kW-PV,850kW-WT,800kW-DG, 1212 no. of batteries and 591 kW converter along with TLC-2000kW, having minimum NPC: 0.272/kWh and highest RF:91.6% can provide 92% reliable power supply to onsite load demand of 4502.95kWh/day with 70% renewable sources in the considered site. This paper also presents a sensitivity analysis of the hybrid system with variations in load demand, diesel fuel price, project lifetime, and interest rate
Grey wolf optimisation algorithm for solving distribution network reconfiguration considering distributed generators simultaneously
No full textThis article represents an application of the grey wolf optimisation (GWO) algorithm to solve the most optimistic combinatorial problems for optimal distribution network reconfiguration (DNR) and allocation of distributed generators (DGs) in a system. In this work, a metaheuristics algorithm is utilised to minimise the active power losses (APL) and enhance the voltage profile. Various scenarios were considered in this context to compare the performance of the proposed algorithm under voltage and current capacity constraints. Furthermore, a detailed validation via comparison of the results is being carried out with other methods from the exhaustive literature. The proposed algorithm reduces the APL by 63.13%, 56.19%, and 34.27% with DNR in IEEE 33, 69 and 118-bus systems. Similarly, APL reduction by 69.61%, 82.09%, and 36.08% with DNR considering DGs simultaneously. The results show that the proposed algorithm is an effective and promising method to solve problems similar to this work
Impact of Distributed Generation on Distribution System Under Fault and Islanding Condition
No full text
REALIZING A SINGLE-STAGE HYBRID PV SYSTEM USING BATTERY CURRENTSHARING POWER DECOUPLING METHOD
No full textConventionally, the single-stage grid-connected PV inverter needs a large PV-side electrolytic capacitor to suppress the doubleline frequency current ripple to keep the PV operating at maximum power point (MPP). However, the short lifetime electrolytic capacitor will reduce the PV inverter’s reliability dramatically. In order to overcome the above problem, a novel battery currentsharing power decoupling (BCSPD) method for hybrid photovoltaic (PV) power systems is proposed in this paper. The proposed BCSPD circuit is parallel-connected with the string PV module to achieve as a single-stage topology. Thus, a high power conversation efficiency can be obtained. The current-injection method is adapted to solve the current ripple problem. Therefore, the required capacitance in PV side can be greatly reduced, so long-life film capacitors can be used instead of electrolytic capacitors. In addition, the battery storage system with the droop control is also used to realize the power regulation function to meet the requirements of actual applications. A 1200 W prototype was designed and implemented to assess the system performance. Experimental results show that the proposed system can track MPP, regulate the load power condition, and reduce current ripple
Load frequency control of interconnected power system using cuckoo search algorithm
Get PDFThis paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a two-area thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions
Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability
No full textAbstract Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as “Porpoising”. This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems
Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement
Get PDFThis paper presents an implementation of the hybrid Cuckoo search and Grey wolf (CS-GWO) optimization algorithm for solving the problem of distribution network reconfiguration (DNR) and optimal location and sizing of distributed generations (DGs) simultaneously in radial distribution systems (RDSs). This algorithm is being used significantly to minimize the system power loss, voltage deviation at load buses and improve the voltage profile. When solving the high-dimensional datasets optimization problem using the GWO algorithm, it simply falls into an optimum local region. To enhance and strengthen the GWO algorithm searchability, CS algorithm is integrated to update the best three candidate solutions. This hybrid CS-GWO algorithm has a more substantial search capability to simultaneously find optimal candidate solutions for problem. Furthermore, to validate the effectiveness and performances of the proposed hybrid CS-GWO algorithm is being tested and evaluated for standard IEEE 33-bus and 69-bus RDSs by considering different scenarios
