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Deployment of Renewable Embedded Generation and Unified Power Quality Conditioner in Distribution System using Firefly Algorithm
Abstract
The efficiency and operation of current distribution systems have been enhanced by the insertion of renewable distributed generation (RDG). However, the placement of DG does not satisfy the network’s need for reactive power, which keeps the voltage of the buses at a level that maximizes the uncontrolled real and reactive variations of power systems. This paper proposed the optimal allocation of DG and Unified Power Quality Conditioner (UPQC) simultaneously to improve the performance of an active distribution system. The most advanced custom power device is the UPQC which combined with the capability of shunt and series compensator features allows for voltage and current compensation in distribution systems. A suitable optimization method is needed to address the challenge of selecting the capacity and position of these compensators. The Firefly Algorithm (FA) is a promising solution to the challenges of multi-objective optimization. The intended objective is active and reactive power loss reduction while improving the voltage profile without violating any system constraints. The effectiveness of the proposed optimal allocation of DG/UPQC using the FA method was evaluated by comparing it to the allocation of the DG system only and the base case system scenarios, respectively. The results revealed a significant percentage reduction in active and reactive power losses, reaching 72.01% and 66.57% with the optimal DG/UPQC allocation combination, respectively. In comparison to the Artificial Bee Colony Optimization (ABC) method, the results revealed the FA method is more efficient regarding both convergence speed and solution quality. The MATLAB 2021b environment served as the platform for the simulation, and it was tested it using the IEEE 33-bus radial distribution system method.
Nowadays, the globe faces an urgent need to switch to sustainable and renewable sources of energy due to the rising concern over climate change and the finite supply of fossil fuels. Technologies for producing energy from renewable sources have become a viable option for achieving sustainable development and addressing environmental issues. This edited book provides a collection and overview of the role, advances, and different paradigms that renewable energy plays in promoting sustainable development, stressing both the potential advantages and difficulties. In this book, 68 are included, which represent the different types of applications in the area of renewable power for sustainable growth such as: (1) Smart Grid Technologies and Applications (5 chapters); (2) Renewable Power Systems including Solar PV, Solar Thermal, and Wind (10 chapters); (3) Power Generation, Transmission and Distribution (8 chapters); (4) Transportation Electrification and Automotive Technologies (10 chapters); (5) Power Electronics and Applications in Renewable Power System (8 chapters); (6) Energy Management and Control System (7 chapters); (7) Energy Storage in Modern Power System (5 chapters); (8) Active Distribution Network (4 chapters); (9) Artificial Intelligence in Renewable Power Systems (5 chapters); and (10) Cyber-Physical Systems and Internet of Things in Smart Grid and Renewable Power (5 chapters).
This paper proposes the implementation of a Bacterial Foraging Algorithm (BFA) based approach for optimal positioning and sizing of Universal Power Quality Conditioner (UPQC) in a radial distribution network. The objective here is to demonstrate the strength and capability of the approach in the placement of UPQC in not just standard test networks, but also in practical power distribution networks. A simple and direct power flow computation is performed to determine the network base-case scenario. Based on the power flow outcome, the network bus voltage deviation VD is formulated and combined with the total active power loss PLoaa(Total) to form a multi-objective function needed by the BFA in order to improve voltage stability and minimize losses, while at the same time maintaining the network constraints. The BFA approach is implemented on a practical 50-bus Canteen Feeder for steady-state normal loading condition. The performance of the technique on the standard IEEE 33-bus test network as established in an earlier literature is once again reported in this paper, after which the results obtained from the practical distribution feeder analysis is presented. Simulation outcomes from MATLAB R2017a virtual environment showed that the installation of UPQC in the practical distribution feeder using the BFA method has improved the overall feeder voltage profile and reduce the active power loss by 9.78 and 26.21% respectively as compared to the network base-case scenario.
Numerous potential advantages to the requirements and effectiveness of the supplied electricity can be accomplished by the installation of distributed generation units. In order to take full advantage of these benefits, it is essential to position the Distributed Generation (DG) units in appropriate locations. Otherwise, their installation may have an adverse effect on the quality of energy and system operation. Several optimization techniques have been created over the years to optimize distributed generation integration. Optimization techniques are therefore constantly changing and have been the main attention of many fresh types of research lately. This article evaluates cutting-edge techniques of optimizing the issue of positioning and sizing distributed generation units from renewable energy sources based on recent papers that have already been applied to distribution system optimization. Furthermore, this article pointed out the environmental, economic, technological and regulatory drivers that lead to a rapid interest in the DG system based on renewable sources. A summary of popular meta-heuristic optimization tools discussed in table form with merits and demerits to increase fresh prospective paths to multi-approach that have not yet been studied.
The optimal operation of current distribution networks has a great importance due to growing electrical demand and significant power losses. In this paper, the optimal allocation of unified power quality conditioner (UPQC) in smart grid with responsive loads is investigated as an appropriate solution to reduce power losses. Also, in order to consider different consumption patterns and to predict the demand with the lowest error, different linear and nonlinear models of responsive loads are taken into account. New pricing method in demand response programs (DRPs) is another concept which is developed in the paper by which optimal electricity prices in DRP during peak, off-peak, and valley periods are determined. Moreover, DRPs are prioritized by the Topsis method based on the different Utility’s policies. The final proposed model has been applied on the IEEE 12-bus, IEEE 33-bus, and the practical 94-bus Portuguese RDS distribution system. The results show that the UPQC allocation in the presence of DRPs is a win–win game both for the Utility and for customers.
Distributed Generation (DG) offers the reliable and economic source of electricity to consumers. These are connected directly to the distribution system at consumer load points. Integration of DG units into an existing system has significantly high importance due to its innumerable advantages. However, Optimal DG (ODG) allocation and sizing is always a challenging task for utilities as well as consumers. The major objective of ODG allocation and sizing is to improve system overall efficiency with minimum power loss, maximum system security, voltage stability, and reliability. Analytical techniques are performing well for small and simple systems, not suitable for a system with large and complex networks. However, various meta-heuristic techniques are performing better in terms of accuracy and convergence for extensively large and complex networks. A hybrid optimization is a combination of two or more optimization techniques. This technique offers efficient and reliable global optimum solutions for complex multi-objective problems. In this context, a comprehensive literature review of DG fundamentals and the different technical approaches for DG integration into the distribution system are analyzed here. Furthermore, an attempt has been made for comparison of analytical, classical (non-heuristic), meta-heuristic and hybrid optimization techniques with respect to objective function, test system, advantages, and disadvantages. This present study will give in-depth knowledge and acts as a forthright reference for imminent investigators and investors for ODG allocation and sizing in a distribution system.
This paper introduces a new optimization method to determine the optimal allocation of Unified Power Quality Conditioner (UPQC) in the distribution systems. UPQC is a versatile Custom Power Device (CPD) to solve problems related to voltage and current by the series and shunt compensator in the distribution systems. The task of UPQC highlighted in this paper is the required load reactive power is provided by both the series and shunt compensators. The UPQC's steady state compensation capability has given a solution for providing reactive power compensation in large distribution systems. The optimization method adopted is Moth Flame Optimization (MFO). The best location and series compensator voltage are determined using MFO. The voltage injected by the series compensator and reactive power injected by the shunt compensator is incorporated in the load flow method. The effectiveness of the proposed method is validated with standard distribution systems. © 2018 Institute of Advanced Engineering and Science. All rights reserved.
The paper presents a decision-making algorithm that has been developed for the optimum size and placement of distributed generation (DG) units in distribution networks. The algorithm that is very flexible to changes and modifications can define the optimal location for a DG unit (of any type) and can estimate the optimum DG size to be installed, based on the improvement of voltage profiles and the reduction of the network’s total real and reactive power losses. The proposed algorithm has been tested on the IEEE 33-bus radial distribution system. The obtained results are compared with those of earlier studies, proving that the decision-making algorithm is working well with an acceptable accuracy. The algorithm can assist engineers, electric utilities, and distribution network operators with more efficient integration of new DG units in the current distribution networks.
Due to rapid depletion of fossil fuels availability and huge environmental pollution, focus is now changing from traditional method of power generation to the non-conventional DERs located at distribution voltage level. Technological advancement and more researches in the use of DERs result in the formation of microgrids and active distribution network. Small DER units when placed in a network near to load, makes the network stable as it can work in islanding mode in case of any fault outside the network. This paper proposes a scheme for reduction in losses and improvement of bus voltages in the active distribution network. A DG in the form of small renewable energy resources such as solar PV, wind, biomass, is placed optimally for reduction of losses in the network. However, placement of DG does not result in fulfilment of reactive power needs of the network, resulting in under voltage at several buses. This under voltage problem is solved by the optimal placement of DSTATCOM. DLF technique is used in this paper for load flow calculations and LSF along with voltage deviation is used in objective function for optimal location of DG on MATLAB platform. The methodology is tested on 33-bus radial distribution system
This paper proposes a new approach to determine the optimal location and sizing of Distributed Generation (DG) and Distribution STATic COMpensator (DSTATCOM) simultaneously in the distribution network. The objective function is formulated to minimize the total power losses of the system subjected to equality and inequality constraints. Loss sensitivity factor (LSF) and Voltage Stability Index (VSI) are used to predetermine the optimal location of DG and DSTATCOM, respectively. Recently developed nature-inspired cuckoo search algorithm (CSA) has been used to determine the optimal size of both DG and DSTATCOM. In the present work, five different cases have been considered during DG and DSTATCOM placement to access the performance of the proposed technique. To check the feasibility, the proposed method is tested on IEEE 12-bus, 34-bus, and 69-bus radial distribution system and the results were compared with other existing techniques.
This chapter describes the linear and nonlinear models of the power plant, and the basic parts and the operation of generators are also described. The dynamic responses of the hydraulic and guide vanes are discussed. Advances in primary speed/load control of hydroelectric plant are discussed, and the development of the turbine-generator control is reviewed.
Differential evolution (DE) algorithm is used to determine optimal location of unified power quality conditioner (UPQC) considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF) defined for improving of voltage and current profiles, reducing power loss and minimizing the investment costs considering the OF's weighting factors. Hence, a steady-state model of UPQC is derived to set in forward/backward sweep load flow. Studies are performed on two IEEE 33-bus and 69-bus standard distribution networks. Accuracy was evaluated by reapplying the procedures using both genetic (GA) and immune algorithms (IA). Comparative results indicate that DE is capable of offering a nearer global optimal in minimizing the OF and reaching all the desired conditions than GA and IA.
Custom power devices (CPD) are used to protect conventional and sensitive loads against power quality disturbances such as voltage sag/swell and harmonic distortion in power systems. The proper placement of CPDs has an important effect on the quality of improvement and ensures that the total costs are minimal in accordance with maximum efficiency. This paper presents a survey of the literature in the last decade that have focused on the various optimization techniques applied to determine optimal placement and size of CPD.
Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly algorithm is superior to existing metaheuristic algorithms. Finally we will discuss its applications and implications for further research.
Modern optimisation algorithms are often metaheuristic, and they are very
promising in solving NP-hard optimization problems. In this paper, we show how
to use the recently developed Firefly Algorithm to solve nonlinear design
problems. For the standard pressure vessel design optimisation, the optimal
solution found by FA is far better than the best solution obtained previously
in literature. In addition, we also propose a few new test functions with
either singularity or stochastic components but with known global optimality,
and thus they can be used to validate new optimisation algorithms. Possible
topics for further research are also discussed.
This paper proposed a new methodology based on nature-enthused meta-heuristic optimization algorithm named as whale optimization algorithm (WOA), which can significantly envisage problems for simultaneous allocation of distributed generation (DG) and Distribution STATic COMpensator (DSTATCOM) in the radial distribution systems (RDS). In the proposed method, optimal locations and sizing of the DG and DSTATCOM can be determined by loss sensitivity factor and WOA, respectively. The objective function of the proposed method is to minimize the system's total power losses and total operating cost of DG and DSTATCOM. The proposed method is applied to well-known IEEE 33-bus and large 136-bus RDS. The attained simulation results and comparison of different cases considered leads to allocation of DG and DSTATCOM combination resulting in significant power loss reduction with good voltage profile enhancement.
Maintaining a stable level of power quality in the distribution network is a growing challenge due to increased use of power electronics converters in domestic, commercial and industrial sectors. Power quality deterioration is manifested in increased losses; poor utilization of distribution systems; mal-operation of sensitive equipment and disturbances to nearby consumers, protective devices, and communication systems. However, as the energy-saving benefits will result in increased AC power processed through power electronics converters, there is a compelling need for improved understanding of mitigation techniques for power quality problems. This timely book comprehensively identifies, classifies, analyses and quantifies all associated power quality problems, including the direct integration of renewable energy sources in the distribution system, and systematically delivers mitigation techniques to overcome these problems. Key features: • Emphasis on in-depth learning of the latest topics in power quality extensively illustrated with waveforms and phasor diagrams. • Essential theory supported by solved numerical examples, review questions, and unsolved numerical problems to reinforce understanding. • Companion website contains solutions to unsolved numerical problems, providing hands-on experience. Senior undergraduate and graduate electrical engineering students and instructors will find this an invaluable resource for education in the field of power quality. It will also support continuing professional development for practicing engineers in distribution and transmission system operators.
This book presents a new problem-solving learning approach to power quality and modern mitigation techniques based on the authors??? experience. Power quality issues have become a popular topic recently because of the rapid increase in power electronic systems in households, industry, and commercial energy systems. The fast growth of renewable energy and distributed generation causes additional power quality problems. On the other hand, low power quality leads to increased loss and poor utilization of power distribution grids and malfunctions of sensitive devices that can lead to their exclusion. This book discusses both classification and analysis of all problems related to power quality. Power Quality: Problems and Mitigation Techniques also presents a systematic methodology for power quality and techniques to reduce and mitigate problems through practical case studies.
A survey on unified power quality conditioner for power quality improvement
- P M Kadam
- B E Kushare
Fire fly swarm : metaheuristic swarm intelligence technique for mathematical optimization
- G K Durbhaka
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An analysis of load management system by using UPQC for distribution network. Emerging trends expert application and security advance intelligence system computer
- D Jayalakshmi
- S Sankar
- M Venkateshkumar