Multi-stage Fuzzy Power System Stabilizer based on Modified Shuffled Frog Leaping Algorithm

This paper presents a new strategy based on Multi-stage Fuzzy (MSF) PID controller for damping Power System Stabilizer (PSS) in multi-machine environment using Modified Shuffled Frog Leaping (MSFL) algorithm. The proposed technique is a new meta-heuristic algorithm which is inspired by mating procedure of the honey bee. Actually, the mentioned algorithm is used recently in power systems which demonstrate the good reflex of this algorithm. Also, finding the parameters of PID controller in power system has direct effect for damping oscillation. Hence, to reduce the design effort and find a better fuzzy system control, the parameters of proposed controller is obtained by MSFL that leads to design controller with simple structure that is easy to implement. The effectiveness of the proposed technique is applied to Single machine connected to Infinite Bus (SMIB) and IEEE 3-9 bus power system. The proposed technique is compared with other techniques through ITAE and FD

Optimal Allocation Of Distributed Renewable Energy Sources In Power Distribution Networks

In this dissertation study, various methods for optimum allocation of renewable distributed generators (DGs) in both balanced and unbalanced distribution networks have been proposed, developed, and tested. These methods were developed with an objective of maximizing several advantages of DG integration into the current distribution system infrastructure. The first method addressed the optimal sitting and sizing of DGs for minimum distribution power losses and maximum voltage profile improvement of distribution feeders. The proposed method was validated by comparing the results of a balanced distribution system with those reported in the literature. This method was then implemented in a co-simulation environment with Electric Power Research Institute\u27s (EPRI) OpenDSS program to solve a three phase optimal power flow (TOPF) problem for optimal location and sizing of multiple DGs in an unbalanced IEEE-123 node distribution network. The results from this work showed that the better loss reduction can be achieved in less computational time compared to the repeated load flow method. The second and third methods were developed with the goal of maximizing the reliability of distribution networks by optimally sitting and sizing DGs and reclosers in a distribution network. The second method focused on optimal allocation of DGs and reclosers with an objective of improving reliability indices while the third method demonstrated the cost based reliability evaluation. These methods were first verified by comparing the results obtained in a balanced network with those reported in literature and then implemented on a multi-phase unbalanced network. Results indicated that optimizing reclosers and DGs based on the reliability indices increases the total cost incurred by utilities. Likewise, when reclosers and DG were allocated to reduce the total cost, the reliability of the distribution system decreased. The fourth method was developed to reduce the total cost incurred by utilities while integrating DGs in a distribution network. Various significant issues like capital cost, operation and maintenance cost, customer service interruption cost, cost of the power purchased from fossil fuel based power plants, savings due to the reduction in distribution power losses, and savings on pollutant emissions were included in this method. Results indicated that integrating DGs to meet the projected growth in demand provides the maximum return on the investment. Additionally, during this project work an equivalent circuit model of a 1.2 kW PEM fuel cell was also developed and verified using electro impedance spectroscopy. The proposed model behaved similar to the actual fuel cell performance under similar loading conditions. Furthermore, an electrical interface between the geothermal power plant and an electric gird was also developed and simulated. The developed model successfully eliminated major issues that might cause instability in the power grid. Furthermore, a case study on the evaluation of geothermal potential has been presented

Integration of Energy Storage and Distributed Generation (DG) in Distribution Systems: Economic Analysis and Development Perspective

This paper sheds light on distributed generation (DG) and energy storage and their impacts on electricity distribution networks. The purpose is to consider the various technologies of DG and energy storage and their financial and dynamic influence on the distribution network performance. In this paper, some different business cases in the U.S. related to energy storage and DG are investigated. One of these cases is related to Hawaiian Electric CO. One of the goals of Hawaiian Electric Co. for 2030 is to provide at least 65 percent of its electricity from renewable resources and working on providing sufficient energy storage. The company is considering energy storage project proposals on Oahu in order to provide their services by 2017. The paper will provide a look inside the company and how they are managing their existing projects and their future plans

Integration of Energy Storage and Distributed Generation (DG) in Distribution Systems: Economic Analysis and Development Perspective

This paper sheds light on distributed generation (DG) and energy storage and their impacts on electricity distribution networks. The purpose is to consider the various technologies of DG and energy storage and their financial and dynamic influence on the distribution network performance. In this paper, some different business cases in the U.S. related to energy storage and DG are investigated. One of these cases is related to Hawaiian Electric CO. One of the goals of Hawaiian Electric Co. for 2030 is to provide at least 65 percent of its electricity from renewable resources and working on providing sufficient energy storage. The company is considering energy storage project proposals on Oahu in order to provide their services by 2017. The paper will provide a look inside the company and how they are managing their existing projects and their future plans

Upgrading Plan for Conventional Distribution Networks Considering Virtual Microgrid Systems

It is widely agreed that the integration of distributed generators (DGs) to power systems is an inevitable trend, which can help to solve many issues in conventional power systems, such as environmental pollution and load demand increasing. According to the study of European Liaison on Electricity grid Committed Towards long-term Research Activities (ELECTRA), in the future, the control center of power systems might transfer from transmission networks to distribution networks since most of DGs will be integrated to distribution networks. However, the infrastructure of conventional distribution networks (CDNs) has not enough capabilities to face challenges from DG integration. Therefore, it is necessary to make a long-term planning to construct smart distribution networks (SDNs). Although many planning strategies are already proposed for constructing SDNs, most of them are passive methods which are based on traditional control and operating mechanisms. In this thesis, an active planning framework for upgrading CDNs to SDNs is introduced by considering both current infrastructure of CDNs and future requirements of SDNs. Since conventional centralised control methods have limited capabilities to deal with huge amount of information and manage flexible structure of SDNs, virtual microgrids (VMs) are designed as basic units to realise decentralised control in this framework. Based on the idea of cyber-physical-socioeconomic system (CPSS), the structure and interaction of cyber system layer, physical system layer as well as socioeconomic system layer are considered in this framework to improve the performance of electrical networks. Since physical system layer is the most fundamental and important part in the active planning framework, and it affects the function of the other two layers, a two-phase strategy to construct the physical system layer is proposed. In the two-phase strategy, phase 1 is to partition CDNs and determine VM boundaries, and phase 2 is to determine DG allocation based on the partitioning results obtained in phase 1. In phase 1, a partitioning method considering structural characteristics of electrical networks rather than operating states is proposed. Considering specific characteristics of electrical networks, electrical coupling strength (ECS) is defined to describe electrical connection among buses. Based on the modularity in complex network theories, electrical modularity is defined to judge the performance of partitioning results. The effectiveness of this method is tested in three popular distribution networks. The partitioning method can detect VM boundaries and partitioning results are in accord with structural characteristics of distribution networks. Based on the partitioning results obtained in phase 1, phase 2 is to optimise DG allocation in electrical networks. A bi-level optimisation method is proposed, including an outer optimisation and an inner optimisation. The outer optimisation focus on long-term planning goals to realise autonomy of VMs while the inner optimisation focus on improving the ability of active energy management. Both genetic algorithm and probabilistic optimal power flow are applied to determine the type, size, location and number of DGs. The feasibility of this method is verified by applying it to PG&E 69-bus distribution network. The operation of SDNs with VMs is a very important topic since the integration of DGs will lead to bidirectional power flow and fault current variation in networks. Considering the similarity between microgrids and VMs, a hybrid control and protection scheme for microgrids is introduced, and its effectiveness is tested through Power Systems Computer Aided Design (PSCAD) simulation. Although more research is needed because SDNs are more complicated than microgrids, the hybrid scheme has great potential to be applied to VMs

Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids

Reconfiguration and Self-healing Mechanisms in Distribution Systems with High Distributed Generation (DG) Penetration

Recently, interest in Smart Grid (SG) as a tool for modernization and automation of the current distribution system has rapidly increased. This interest can be explained by the common belief that SG technologies greatly enhance system reliability, power quality and overall efficiency. One of the most important objectives of an SG is to accommodate a wide variety of generation options. This objective aligns with the new trends and policies that encourage higher penetration levels of Distributed Generation (DG) according to environmental, regulatory and economical concerns. Most DG units are either renewable or low emission energy sources, thus meeting the Canadian emission portfolios, while they remain attractive for both utilities and customers for different reasons. DG units can postpone large investment in transmission and central generation, reduce energy losses, and increase system reliability and power quality. SG is centered on several objectives such as self-healing, motivating consumers to participate in grid operation, resisting attacks, accommodating a wide variety of DG units and storage devices, and optimizing assets. Yet, one of the main goals of SG is to increase the reliability of power systems. Reliability is a vital factor in power system performance, due to the full dependence of today’s life on electricity and the high cost of system outages, especially for critical loads. Therefore, one of the main salient features of SG is its ability of self-healing. The insertion of DG units changes distribution networks from being passive with unidirectional power flow and a single power source (the primary substation) towards active networks with multi-directional power flow and several power sources (the primary substation, along with DG units). As a result, the interconnection of DG units creates several impacts on different practices such as voltage profile, power flow, power quality, stability, reliability, fault detection, and restoration. Current policies call for the direct disconnection of all DG units once any failure occurs in the network. However, with a high DG power penetration, the utilities cannot operate the system efficiently without the DG units’ support. Furthermore, automatic disconnection of the DG units during faults reduces the expected benefits associated with DG units drastically. Motivated by the above facts, the overall target of this thesis is to introduce distribution system mechanisms to facilitate realizing the concept of Smart Distribution System (SDS) in both normal and emergency modes. In particular, three main functions are dealt with in this research work: distribution network reconfiguration, DG allocation and self-healing. First, for distribution network reconfiguration, a method based on genetic algorithm is presented to address the reconfiguration problem for distribution systems while the effect of load variation and the stochastic power generation of renewable-based DG units are taken into consideration. The presented method determines the annual distribution network reconfiguration scheme considering switching operation costs in order to minimize annual energy losses by determining the optimal configuration for each season of the year. Second, for DG allocation, a joint optimization algorithm has been proposed to tackle the DG allocation and network reconfiguration problems concurrently, as these two issues are inherently coupled. The two problems are dealt with together while the objectives are minimizing the cost, as an economic issue, and greenhouse gas emissions, as an environmental issue. The proposed method takes the probabilistic nature of both the renewable energy resources and loads into account. The last operation function dealt with in this thesis is distribution system restoration. In order to accomplish this function, two stages are presented: In the first stage, numerous practical aspects related to service restoration problem have been investigated. These aspects include variations in the load and customer priorities, price discounts for in-service customers based on their participation in a load-curtailment scheme that permits other customers to be supplied, the presence of manual and automated switches, and the incorporation of DG units (dispatchable and wind-based units) in the restoration process. In the second stage, the smart grid concept and technologies have been applied to construct a self-healing framework to be applied in smart distribution systems. The proposed multi-agent system is designed to automatically locate and isolate faults, and then decide and implement the switching operations to restore the out-of-service loads. Load variation has been taken into consideration to avoid the need for further reconfigurations during the restoration period. An expert-based decision-making algorithm has been used to govern the control agents. The rules have been extracted from the practical issues related to the service restoration problem, discussed in the first stage