26,815 research outputs found

    Distribution Network Planning and Operation With Autonomous Agents

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    With the restructured power system, different system operators and private investors are responsible for operating and maintaining the electricity networks. Moreover, with incentives for a clean environment and reducing the reliance on fossil fuel generation, future distribution networks adopt a considerable penetration of renewable energy sources. However, the uncertainty of renewable energy sources poses operational challenges in distribution networks. This thesis addresses the planning and operation of the distribution network with autonomous agents under uncertainty. First, a decentralized energy management system for unbalanced networked microgrids is developed. The energy management schemes in microgrids enhance the utilization of renewable energy resources and improve the reliability and resilience measures in distribution networks. While microgrids operate autonomously, the coordination among microgrid and distribution network operators contributes to the improvement in the economics and reliability of serving the demand. Therefore, a decentralized energy management framework for the networked microgrids is proposed. Furthermore, the unbalanced operation of the distribution network and microgrids, as well as the uncertainty in the operating modes of the microgrids, renewable energy resources, and demand, are addressed. The second research work presents a stochastic expansion planning framework to determine the installation time, location, and capacity of battery energy storage systems in the distribution network with considerable penetration of photovoltaic generation and data centers. The presented framework aims to minimize the capital cost of the battery energy storage and the operation cost of the distribution network while ensuring the security of energy supply for the data centers that serve end-users in the data network as well as the reliability requirements of the distribution network. The third research work proposes a coordinated expansion planning of natural gas-fired distributed generation in the power distribution and natural gas networks considering demand response. The problem is formulated as a distributionally robust optimization problem in which the uncertainties in the photovoltaic power generation, electricity load, demand bids, and natural gas demand are considered. The Wasserstein distance metric is employed to quantify the distance between the probability distribution functions. The last research work proposes a decentralized operation of the distribution network and hydrogen refueling stations equipped with hydrogen storage, electrolyzers, and fuel cells to serve hydrogen and electric vehicles. The uncertainties in the electricity demands, PV generation, hydrogen supply, and hydrogen demands are captured, and the problem is formulated as a Wasserstein distance-based distributionally robust optimization problem. The proposed framework coordinates the dispatch of the distributed generation in the distribution network with the hydrogen storage, electrolyzer, and fuel cell dispatch considering the worst-case probability distribution of the uncertain parameters. The proposed frameworks limit the information shared among these autonomous operators using Benders decomposition

    Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

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    The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

    Scenarios for the development of smart grids in the UK: literature review

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    Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

    Modeling a cooperation environment for flexibility enhancement in smart multi-energy industrial systems

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    Environmental aspects have been highlighted in architecting future energy systems where sustainable development plays a key role. Sustainable development in the energy sector has been defined as a potential solution for enhancing the energy system to meet the future energy requirements without interfering with the environment and energy provision. In this regard, studying the cross-impact of various energy vectors and releasing their inherent operational flexibility is main topic. Thecoordinationofvariousenergyvectorsundertheconceptofmulti-energysystem (MES)hasintroducednewsourcesofoperationalflexibilitytothesystemmanagers. MES considers both interactions among the energy carriers and the decision makers in an interdependent environment to increase the total efficiency of the system and reveal the hidden synergy among energy carriers. This thesis addresses a framework for modeling multi-energy players (MEP) that are coupled based on price signal in multi-energy system (MES) in a competitive environment. MEP is defined as an energy player who can consume or deliver more than one type of energy carriers. At first, the course of evolution for the energy system from today independent energy systems to a fully integrated MES is presented and the fractal structure is described for of MES architecture. Moreover, the operational behavior of plug-in electric vehicles’ parking lots and multi-energy demands’ external dependency are modeled in MES framework to enhance the operational flexibility of local energy systems (LES). In the fractal environment, there exist conflicts among MEPs’ decision making in a same layer and other layers. Realizing the inherent flexibility of MES is the main key for modeling the conflicts in this multi-layer structure. The conflict between two layers of players is modeled based on a bi-level approach. In this problem, the first level is the MEP level where the player maximizes its profit while satisfying LES energy exchange. The LES’s exchange energy price is the output of this level. In the lower level, the LESs schedule their energy balance, based on the upper level input price signal. The problem is transformed into a mathematical program with equilibrium constraint (MPEC) through duality theory. In the next step, high penetration of multi-energy players in the electricity market is modeled and their impacts on electricity market equilibrium are investigated. In such a model, MEP participates in the local energy and wholesale electricity markets simultaneously. MEP and the other players’ objectives in these two markets conflict with each other. Each of these conflicts is modeled based on bi-level programming. The bi-level problems are transformed into a single level mixed-integer linear problem by applying duality theory

    Energy Access Scenarios to 2030 for the Power Sector in Sub-Saharan Africa

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    In order to reach a goal of universal access to modern energy services in Africa by 2030, consideration of various electricity sector pathways is required to help inform policy-makers and investors, and help guide power system design. To that end, and building on existing tools and analysis, we present several ‘high-level’, transparent, and economy-wide scenarios for the sub-Saharan African power sector to 2030. We construct these simple scenarios against the backdrop of historical trends and various interpretations of universal access. They are designed to provide the international community with an indication of the overall scale of the effort required. We find that most existing projections, using typical long-term forecasting methods for power planning, show roughly a threefold increase in installed generation capacity occurring by 2030, but more than a tenfold increase would likely be required to provide for full access – even at relatively modest levels of electricity consumption. This equates to approximately a 13% average annual growth rate, compared to a historical one (in the last two decades) of 1.7%.Energy Access, Power System Planning, Sub-Saharan Africa

    Review of trends and targets of complex systems for power system optimization

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    Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107
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