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

Advancements in Enhancing Resilience of Electrical Distribution Systems: A Review on Frameworks, Metrics, and Technological Innovations

This comprehensive review paper explores power system resilience, emphasizing its evolution, comparison with reliability, and conducting a thorough analysis of the definition and characteristics of resilience. The paper presents the resilience frameworks and the application of quantitative power system resilience metrics to assess and quantify resilience. Additionally, it investigates the relevance of complex network theory in the context of power system resilience. An integral part of this review involves examining the incorporation of data-driven techniques in enhancing power system resilience. This includes the role of data-driven methods in enhancing power system resilience and predictive analytics. Further, the paper explores the recent techniques employed for resilience enhancement, which includes planning and operational techniques. Also, a detailed explanation of microgrid (MG) deployment, renewable energy integration, and peer-to-peer (P2P) energy trading in fortifying power systems against disruptions is provided. An analysis of existing research gaps and challenges is discussed for future directions toward improvements in power system resilience. Thus, a comprehensive understanding of power system resilience is provided, which helps in improving the ability of distribution systems to withstand and recover from extreme events and disruptions

Microgrids

Integration of renewable energy sources in the electrical power system is key for enabling the decarbonization of that system. The connection of renewable generation to the electrical system is being performed in a centralized form (large renewable power plants like wind or solar power plants connected at the transmission system) and in a decentralized manner (through the connection of dispersed generation connected at the distribution system). The connection of renewable generation at distribution levels, together with other generating sources as well as energy storage systems (the so-called DER, Distributed Energy Resources) close to consumption sites, is promoting the development of microgrids: DER installations that have the capability to operate grid connected and grid isolated. The uncertainty and variability of the renewable energy sources that integrate microgrids, as well as the need for coordination with other energy sources, pose challenges in the operation, protection, control, and planning of microgrids. The five selected papers published in this Special Issue propose solutions to address these challenges.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.1 - Per a 2030, garantir l’accés universal a serveis d’energia assequibles, confiables i modernsObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.2 - Per a 2030, augmentar substancialment el percentatge d’energia renovable en el con­junt de fonts d’energiaPostprint (published version

Microgrid Energy Management

In IEEE Standards, a Microgrid is defined as a group of interconnected loads and distributed energy resources with clearly defined electrical boundaries, which acts as a single controllable entity with respect to the grid and can connect and disconnect from the grid to enable it to operate in both grid-connected or island modes. This Special Issue focuses on innovative strategies for the management of the Microgrids and, in response to the call for papers, six high-quality papers were accepted for publication. Consistent with the instructions in the call for papers and with the feedback received from the reviewers, four papers dealt with different types of supervisory energy management systems of Microgrids (i.e., adaptive neuro-fuzzy wavelet-based controls, cost-efficient power-sharing techniques, and two-level hierarchical energy management systems); the proposed energy management systems are of quite general purpose and aim to reduce energy usages and monetary costs. In the last two papers, the authors concentrate their research efforts on the management of specific cases, i.e., Microgrids with electric vehicle charging stations and for all-electric ships

A review of co-optimization approaches for operational and planning problems in the energy sector

This paper contributes to a comprehensive perspective on the application of co-optimization in the energy sector – tracking the frontiers and trends in the field and identifying possible research gaps – based on a systematic literature review of 211 related studies. The use of co-optimization is addressed from a variety of perspectives by splitting the studies into ten key categories. Research has consistently shown that co-optimization approaches can be technically challenging and it is usually a data-intensive procedure. Overall, a set of techniques such as relaxation, decomposition and linear approaches have been proposed for reducing the inherent nonlinear model's complexities. The need to coordinate the necessary data from multiples actors might increase the complexity of the problem since security and confidentiality issues would also be put on the table. The evidence from our review seems to suggest a pertinent role for addressing real-case systems in future models instead of using theoretical test cases as considered by most studies. The identified challenges for future co-optimization models include (i) dealing with the treatment of uncertainties and (ii) take into account the trade-offs among modelling fidelity, spatial granularity and geographical coverage. Although there is also a growing body of literature that recognizes the importance of co-optimization focused on integrating supply and demand-side options, there has been little work in the development of co-optimization models for long-term decision-making, intending to recognize the impact of short-term variability of both demand and RES supply and well suited to systems with a high share of RES and under different demand flexibility conditions. The research results represent a further step towards the importance of developing more comprehensive approaches for integrating short-term constraints in future co-optimized planning models. The findings provide a solid evidence base for the multi-dimensionality of the co-optimization problems and contriThis work is supported by the National Council for Scientific and Technological Development (CNPq), Brazil. This work has been supported by FCT – Fundaça˜o para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

A comprehensive review of demand side management in distributed grids based on real estate perspectives

A major challenge in renewable energy planning and integration with existing systems is the management of intermittence of the resources and customer demand uncertainties that are attributed to climates. In emerging distributed grids, state-of-the-art optimization techniques were used for cost and reliability objectives. In the existing literature, power dispatch and demand side management schemes were implemented for various techno-economic objectives. In renewable energy-based distributed grids, power dispatch is strategic to system operations. However, demand side management is preferred, as it allows more options for customer participation and active management of energy in buildings. Moreover, the demand side management can simply follow supplies. This paper investigates the implications of demand side management as it affects planning and operations in renewable energy-based distributed grids. Integration of demand side management in customer-oriented plans such as the time-of-use and real-time-pricing on residential and commercial demands is conceptualised to ensure effective customer participation which maintains the valued comforts. Moreover, the optimised tariff integrated demand side management implementations based on the utility-initiated demand response programmes are envisaged to offset conflicting objectives of the economy and customer comforts within residential and commercial demands and are also viewed as a step towards efficient management of energy in buildings

Advances in Theoretical and Computational Energy Optimization Processes

The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes

Microgrid Enabling Towards the Implementation of Smart Grids

Smart grids have emerged as dominant platforms for effectively accommodating high penetration of renewable-based distributed generation (DG) and electric vehicles (EVs). These smart paradigms play a pivotal role in the advancement of distribution systems and pave the way for active distribution networks (ADNs). However, the large number of smart meters deployed in the distribution system (e.g., 200 million smart meters will be installed in Europe by 2020) represents one of the main challenges facing the management and control of distribution networks and thus the enabling of smart grids. In addition to the data tsunami flooding central controllers, the concerns about privacy and system vulnerability are fast becoming a key restraint for the implementation of the smart grids. These concerns are prompting utilities to be more reluctant to adopt new techniques, leaving the distribution system mired in relatively old-fashioned routines. Microgrids provide an ideal paradigm to form smart grids, thanks to their limited size and ability to ‘island’ when supplying most of their loads during emergencies, which improves system reliability. However, preserving load-generation balance is comprehensively challenging, given that microgrids are dominated by renewable-based DGs, which are characterized by their probabilistic nature and intermittent power. Although microgrids are now well-established and have been extensively studied, there is still some debate over having microgrids that are solely ac or solely dc, with the consensus tending toward hybrid ac-dc microgrids. Furthermore, while some research has addressed using solely ac microgrids, the planning of hybrid ac-dc microgrids has not yet been investigated, despite the many benefits these types of microgrids offer. Additionally, developing steady-state analysis tools capable of handling grid-connected mode and islanded mode for the operation of ac microgrids and hybrid ac-dc microgrids still has uncertainties about their computational burden, complexity, and convergence. The high R/X ratio characterized distribution systems result in ill-condition that hinders the convergence of conventional Newton Raphson (NR) techniques. Moreover, calculating the inversion of the Jacobian matrix that is formed from the calculation of derivatives adds to the complexity of these techniques. Therefore, developing a simple, accurate, and fast steady-state analysis tool is crucial for enabling microgrids and hence smart grids. Driven by the aforementioned challenges, the broad goal of this thesis is to enable microgrids as building clusters to smooth and accelerate the realization of smart grids. Achieving this objective involves a number of stages, as follows: 1) The development of probabilistic models for loads and renewable DG-based output power. These models are then integrated with the load flow analysis techniques to form a probabilistic power flow (PPF) tool. 2) The proposal of a novel operational v philosophy that divides existing bulky grids into manageable clusters of self-adequate microgrids that adapt their boundaries to keep load-generation balance at different operating scenarios. 3) The proposal of planning a framework for the newly constructed grids as hybrid ac-dc microgrids with minimum levelized investment costs and consideration of the probabilistic nature of load and renewable generation. 4) The development of a branch-based power flow algorithm for steady-state analysis of ac microgrids and hybrid ac-dc microgrids