Management of Islanded Operation of Microgirds

Distributed generations with continuously growing penetration levels offer potential solutions to energy security and reliability with minimum environmental impacts. Distributed Generations when connected to the area electric power systems provide numerous advantages. However, grid integration of distributed generations presents several technical challenges which has forced the systems planners and operators to account for the repercussions on the distribution feeders which are no longer passive in the presence of distributed generations. Grid integration of distributed generations requires accurate and reliable islanding detection methodology for secure system operation. Two distributed generation islanding detection methodologies are proposed in this dissertation. First, a passive islanding detection technique for grid-connected distributed generations based on parallel decision trees is proposed. The proposed approach relies on capturing the underlying signature of a wide variety of system events on a set of critical system parameters and utilizes multiple optimal decision tress in a parallel network for classification of system events. Second, a hybrid islanding detection method for grid-connected inverter based distributed generations combining decision trees and Sandia frequency shift method is also proposed. The proposed method combines passive and active islanding detection techniques to aggregate their individual advantages and reduce or eliminate their drawbacks. In smart grid paradigm, microgrids are the enabling engine for systematic integration of distributed generations with the utility grid. A systematic approach for controlled islanding of grid-connected microgrids is also proposed in this dissertation. The objective of the proposed approach is to develop an adaptive controlled islanding methodology to be implemented as a preventive control component in emergency control strategy for microgrid operations. An emergency power management strategy for microgrid autonomous operation subsequent to inadvertent islanding events is also proposed in this dissertation. The proposed approach integrates microgrid resources such as energy storage systems, demand response resources, and controllable micro-sources to layout a comprehensive power management strategy for ensuring secure and stable microgrid operation following an unplanned islanding event. In this dissertation, various case studies are presented to validate the proposed methods. The simulation results demonstrate the effectiveness of the proposed methodologies

Control of an islanded microgrid

This thesis presents a detailed investigative process into the study of the control of an islanded microgrid. This investigation is done through the research and exploration of multiple existing control techniques for the control of a microgrid and then by analysing them to identify the areas where the existing methods can be altered in order to reduce or mitigate common operational issues. The final goal was to use the gathered information to develop an innovative strategy that may be used to control an islanded microgrid. However, due to various challenges faced over the course of the project – this goal was not achieved. In light of this, the aim of this thesis was for it to became a research focused development of a body of work that may be useful or potentially serve as a point of reference for future studies in the control of an islanded microgrid. 1. P & PI Controller Regulation & Response Times 2. Natural Load Sharing Amongst Distributed Generators 3. Secondary Frequency-Load Control Mechanisms 4. Controllable Storage Systems 5. Automated Load Shedding in Microgrids 6. Stabilizer Control Strategies By developing this list of factors and considerations, this thesis project aims to be a useful resource for future studies performed in the topic of islanded microgrid control. The aspiration is that by collating extensive background, theoretical and technical research in this project, the efficiency of those who may want to continue work in this area of study will be improved

Modelling of an Intelligent Microgrid System in a Smart Grid Network

To achieve the goal of decarbonising the electric grid by 2050 and empowering energy citizen, this research focuses on the development of Microgrid (μGrid) systems in Irish environment. As part of the research work, an energy efficient and cost effective solution for μGrid, termed Community-μGrid (C-μGrid) is proposed. Here the users can modify their micro-Generation (μGen) converters to facilitate a single inverter in a C-μGrid structure. The new system could allow: (i) technological advantage of improved Power Quality (PQ); (ii) economic advantage of reduced cost of energy (COE) to achieve sustainability. Analysis of scenarios of C-μGrid (AC) systems is performed for a virtual community in Dublin, Ireland. It consists of (10 to 50) similar type of residential houses and assumes that each house has a wind-based μGen system. It is found that, compared to individual off-grid μGen systems, an off-grid C-μGrid can reduce upto 35% of energy storage capacity. Thus it helps to reduce the COE from €0.22/kWh to 0.16/kWh. In grid connected mode, it can sell excess energy to the grid and thus COE further decreases to €0.11/kWh. Thus a cost-effective C-μGrid is achieved. The proposed system can advance its energy management efficiency through implementation of Demand Side Management (DSM) technique. For the test case, 50% of energy storage capacity could be avoided through DSM technique. It also helps to further decrease the COE by 25%. The C-μGrid system with storage is optimised by implementing the Economic Model Predictive Control (EMPC) approach operating at the pricing level. Emphasis is given to the operational constraints related to the battery lifetime, so that the maintenance and replacement cost would be reduced. This technique could help to improve the battery performance with optimised storage and also reduces the COE of the system by 25%

Hybrid AC/DC Microgrids for Rural Electrification

O objetivo principal desta dissertação é construir um modelo de uma rede híbrida AC/DC no Software Simulink e estudar a maneira como funciona em diferentes condições e cenários. Esta tese divide-se em seis capítulos: o primeiro, a Introdução, explica os principais objetivos, as contribuições, a motivação e como a tese está organizada; o segundo capítulo, o Estado da Arte, reporta-se aos conceitos básicos da eletricidade em áreas rurais, como é que as micro redes e micro redes híbridas funcionam, as suas arquiteturas, modelos utilizados, aplicações, implementação elétrica e a sua importância nestes meios mais afastados das grandes cidades; no capítulo 3 e 4, apresenta-se uma explicação mais sucinta acerca da simulação e testes que se vão realizar; o terceiro capítulo foca-se mais na parametrização dos modelos, nos diferentes cenários para a rede, com o intuito de analisá-la, e na estrutura e implementação das redes AC e DC a ser estudadas; o quarto capítulo explica, de forma mais pormenorizada, como os modelos são construídos e como funcionam as funções de controlo dos mesmos; no capítulo 5, realiza-se uma simulação para cada um dos cenários definidos e é feita uma análise a cada um dos resultados obtidos; no último capítulo, são definidas todas as principais conclusões de todo este projeto.The main objective of this dissertation is to build a hybrid AC/DC microgrid model in the Software Simulink and to study the way it works and performs in different scenarios. This thesis is divided into six chapters: the first one, the Introduction, explains the main objectives, the contributions, the motivation and how the thesis is organized; the second chapter, the State of Art, reports the basic concepts of electricity in rural areas, how the microgrids and hybrid microgrids work, its architecture, models, electrical implementations, applications and the importance of these grids in places that are located far away from the big cities and the main grids; in chapters 3 and 4, it is stated a more succinct explanation about the simulation and tests that will be performed; the third one focuses more on the parametrization of the models, the different scenarios to test and in the structure and implementation of the AC and DC microgrids that are being studied; the fourth chapter explains how models are designed, how they work and how their control functions operate; in chapter 5, the results of the simulation for each scenario are analysed and studied; in the last chapter, all the main conclusions taken from this thesis are defined

Energy Management System for Microgrid System using Improved Grey Wolf Optimization Algorithm

An Energy Management System (EMS) is indispensable to monitor the power flow and load matching inside a microgrid during grid-connected mode (GCM) and islanded modes (IM) of operation. Many conventional optimization algorithms show poor reliability for real time optimization problem solving where an objective function is non-linear. An optimization technique is necessary to reduce the cost of energy obtained from the grid, generated inside the grid, and consumed by the load. This article presents, an optimization scheme based on the improved Grey wolf optimization (GWO) algorithm that considers replacement of wounded/injured wolves of one pack by strong wolves of other pack for an EMS in micro-grid. The GWO optimization algorithm's effectiveness is demonstrated forGCM and IM operation. The proposed GWO shows fast, lost cost and precise optimization of the real time EMS for the grid connected and islanded micro-grid system

HVAC-based hierarchical energy management system for microgrids

With the high penetration of renewable energy into the grid, power fluctuations and supply-demand power mismatch are becoming more prominent, which pose a great challenge for the power system to eliminate negative effects through demand side management (DSM). The flexible load, such as heating, ventilation, air conditioning (HVAC) system, has a great potential to provide demand response services in the electricity grids. In this thesis, a comprehensive framework based on a forecasting-management optimization approach is proposed to coordinate multiple HVAC systems to deal with uncertainties from renewable energy resources and maximize the energy efficiency. In the forecasting stage, a hybrid model based on Multiple Aggregation Prediction Algorithm with exogenous variables (MAPAx)-Principal Components Analysis (PCA) is proposed to predict changes of local solar radiance, vy using the local observation dataset and real-time meteorological indexes acquired from the weather forecast spot. The forecast result is then compared with the statistical benchmark models and assessed by performance evaluation indexes. In the management stage, a novel distributed algorithm is developed to coordinate power consumption of HVAC systems by varying the compressors’ frequency to maintain the supply-demand balance. It demonstrates that the cost and capacity of energy storage systems can be curtailed, since HVACs can absorb excessive power generation. More importantly, the method addresses a consensus problem under a switching communication topology by using Lyapunov argument, which relaxes the communication requirement. In the optimization stage, a price-comfort optimization model regarding HVAC’s end users is formulated and a proportional-integral-derivative (PID)-based distributed algorithm is thus developed to minimize the customer’s total cost, whilst alleviating the global power imbalance. The end users are motivated to participate in energy trade through DSM scheme. Furthermore, the coordination scheme can be extended to accommodate battery energy storage systems (BESSs) and a hybrid BESS-HVAC system with increasing storage capacity is proved as a promising solution to enhance its selfregulation ability in a microgrid. Extensive case studies have been undertaken with the respective control strategies to investigate effectiveness of the algorithms under various scenarios. The techniques developed in this thesis has helped the partnership company of this project to develop their smart immersion heaters for the customers with minimum energy cost and maximum photovoltaic efficiency

Islanding Detection and Power Quality Analysis in Microgrid

芝浦工業大学2019年

Distributed Energy Resources to Improve the Power Quality and to Reduce Energy Costs of a Hybrid AC/DC Microgrid

This chapter deals with microgrids (μGs), i.e., a group of interconnected loads and distributed energy resources that act as a single controllable entity with respect to the grid. The μGs can be classified into AC and DC μGs depending on the characteristics of the supply voltage, with both solutions characterized by advantages and challenges. Recently, hybrid AC/DC μGs have been developed with the aim to exploit the advantages of both AC and DC solutions. Hybrid μGs require being properly controlled to guarantee their optimal behavior, in both grid-connected and islanding mode. In this chapter, we propose an optimal control strategy for a hybrid μG to be realized in an actual Italian industrial facility. The control strategy operates with the aim to simultaneously minimize the energy costs and to compensate waveform distortions. The key result of the chapter consists in evidencing the technical and economic advantages of the proposed solution by means of real-time simulations of the hybrid μG performed through Matlab/Simulink development tool in the different conditions (grid-connected and islanding mode)

Thermostatically Controllable Loads for Primary Frequency Control in Isolated Microgrids

In the last few decades, governments, private investors, and non-governmental organizations have gradually incentivized the integration of Renewable Energy Sources (RESs) and efficient Energy Storage System (ESS) technologies into remote microgrids, in good part because of commitments to counter the harmful effects of greenhouse gas emissions and to reduce dependence on fossil fuels. As a result, hybrid RESs-diesel systems are now being considered as an economic, attractive and reliable option to improve remote microgrids and to offset diesel consumption in isolated communities by displacing generation from conventional units; however, system security and stability is a challenge as the penetration of RESs increases. In this context, it is necessary to explore new mechanisms and control strategies for the provision of frequency support services in order to meet the increased ramp and capacity requirements to integrate RESs into the system effectively. From this standpoint, Demand Response (DR) can be used to increase grid flexibility, improve efficiency, and facilitate the penetration of RESs, by controlling loads in response to predefined control strategies, manipulating the demand profile to provide a service to the system. In particular, DR strategies are well-suited for northern remote communities, where the demand for electricity and heating is much higher than the Canadian residential average consumption due to the harsh climate and poor building energy efficiency. Thermostatically Controllable Loads (TCLs), i.e., Electric Water Heaters (EWHs), Air Conditioners (ACs), and Ground Source Heat Pumps (GSHPs), are ideal candidates to participate in a DR strategy, since they have a high thermal inertia, high-power consumption (among the appliances in a household), and are continuously operating over the day. Therefore, their power consumption can be shifted, or controlled by switching operations without significantly affecting consumer comfort. This is due to the thermal inertia of TCLs, which allow a smooth temperature variation that, in many cases, would be unnoticed by customers. Thus, TCLs provide energy storage capabilities, which are more significant with GSHP systems, and hence, a DR control strategy can use TCLs as thermal energy batteries with similar features than other ESS technologies. Therefore, the research presented in this thesis focus on developing a DR strategy for the provision of primary frequency control in hybrid isolated microgrids using TCLs, i.e., EWHs, ACs, and GSHPs. A comprehensive review of the components, operation, and restrictions of these TCLs is performed in order to develop computationally efficient, simple, and accurate models, which are able to capture the relevant thermodynamic phenomena in dynamic studies. Based on the thermo-electrical characteristics of the developed models, a decentralized DR strategy is designed, which uses local frequency measurements to control the power consumption of the TCLs according to system frequency deviations while considering consumer comfort. The control logic includes ON/OFF commands to modulate the duty cycle of the TCLs to provide primary frequency control and facilitate the integration of RESs. The proposed DR strategy along with the developed thermo-electrical models of TCLs, i.e., EWHs, ACs, and GSHPs, are evaluated using a benchmark hybrid microgrid, which has a significant share of PV generation. In order to resemble realistic conditions, power and hot water consumption simulators are used to generate random demand profiles, while considering a droop control for the diesel genset and a solar PV with a Maximum Power Point Tracking (MPPT) control. Different study cases are conducted to analyze the system frequency response and determine the adequacy of the proposed DR strategy, demonstrating the effectiveness of the proposed TCL controls to provide primary frequency control, and thus facilitate higher penetration of RESs, while reducing costs and maximizing fuel savings