Autonomous Energy Grids

Current frameworks to monitor, control, and optimize large-scale energy systems are becoming increasingly inadequate because of significantly high penetration levels of variable generation and distributed energy resources being integrated into electric power systems; the deluge of data from pervasive metering of energy grids; and a variety of new market mechanisms, including multilevel ancillary services. This paper outlines the concept of autonomous energy grids (AEGs). These systems are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, are extremely secure and resilient (self-healing), and can self-optimize in real time to ensure economic and reliable performance while systematically integrating energy in all forms. AEGs rely on cellular building blocks that can self-optimize when isolated from a larger grid and participate in optimal operation when interconnected to a larger grid. This paper describes the key concepts and research necessary in the broad domains of optimization theory, control theory, big data analytics, and complex system theory and modeling to realize the AEG vision

Designing and simulating smart grids

Growing energy demands and the increased use of renewal energies have changed the landscape of power networks leading to new challenges. Smart Grids have emerged to cope with these challenges by facilitating the integration of traditional and renewable energy resources in distributed, open, and self-managed ways. Innovative models are needed to design energy infrastructures that can enable self-management of the power grid. Software architectures smoothly integrate the software that provides self-management to Smart Grids and their hardware infrastructures. We present a framework to design the software architectures of autonomous Smart Grids in an intuitive domain-oriented way and to simulate their execution by automatically generating the code from the designed autonomous smart grid architectures

Smart multi-terminal DC μ-grids for autonomous zero-net energy buildings: implicit concepts

A decarbonized society involves people living and working in low-energy and low-emission buildings. An a smart multi-Terminal DC μ-grids interconnecting several autonomous zero-net energy buildings allow the transition to a decarbonized economy, however, involves several challenges. This paper describes the interactions between the intrinsic concepts related to development of a smart multi-terminal DC μ-grids for autonomous zero-net energy buildings. Each individual concept provides several advantages but also create several colliding restrictions with other, this paper connects all concepts together considering interactions in other to maximize the total benefit. Also, discussions about the feasibility and impact of the individual concepts on the whole interaction are included

Power quality analysis in off-grid power platform

Research projects in the field of electrical distribution systems are moving to a new philosophy of Smart Grids, where the effort is to use the maximum possible share of power from renewable energy potential. Under this philosophy the emphasis is on energy independence, reliability and safety of operation of energy distribution system. Research in this area leads for example to developing of autonomous local microgrids with the several specific requirements. However, the problem of parameters keeping of quality of electric energy can arise together with increased penetration of distributed generation in microgrids. This problem is caused by decreased short-circuit power of local renewable energy sources, stochastic supply of electric energy from renewable energy sources and operating of active distribution grid in autonomous mode without connection to the external distribution system. General introduction to the power quality evaluation in off-grid power system is introduced in this paper. Initial results from power quality analysis from small off-grids system is presented in this text too

A Control Framework for Autonomous Smart Grids for Space Power Applications

With the National Aeronautics and Space Administration's (NASA) rising interest in lunar surface operations and deep space exploration, there is a growing need to move from traditional ground-based mission operations to more autonomous vehicle level operations. In lunar surface operations, there are periods of time where communications with ground-based mission control could not occur, forcing vehicles and a lunar base to completely operate independent of the ground. For deep space exploration missions, communication latency times increase to greater than 15 minutes making real-time control of critical systems difficult, if not near impossible. These challenges are driving the need for an autonomous power control system that has the capability to manage power and energy. This will ensure that critical loads have the necessary power to support life systems and carry out critical mission objectives. This paper presents a flexible, hierarchical, distributed control methodology that enables autonomous operation of smart grids and can integrate into a higher level autonomous architecture

Design, modelling and valuation of innovative dispatch strategies for energy storage systems

Energy storage has in recent years attracted considerable interest, mainly owing to its potential to support large-scale integration of renewable energy sources (RES). At the same time however, energy storage technologies are called to take over multiple roles across the entire electricity sector, introducing modern applications for both private actors and system operators. In this context, the current thesis focuses on the valuation of emerging energy storage applications, while also proceeding to the design and modelling of novel dispatch strategies, along with the development of financial instruments and support measures for the market uptake of energy storage technologies. In doing so, emphasis is given on mature, bulk energy storage technologies, able to support energy management applications. These include pumped hydro storage, compressed air energy storage and battery technologies. Energy storage applications/dispatch strategies examined are divided into three main categories that focus on private actors, autonomous electricity grids and utility-scale systems. For private energy storage actors, active, profit-seeking participation in energy markets is examined through the evaluation of high-risk arbitrage strategies. Furthermore, the interplay of energy storage and demand side management (DSM) is studied for private actors exposed to increased electricity prices and energy insecurity, designating also the potential for combined strategies of arbitrage and DSM. To reduce the investment risks associated with participation in energy markets, a novel aspect of collaboration between energy storage and RES is accordingly investigated for energy storage investors, proposing the use of storage for the delivery of guaranteed RES power during peak demand periods and stimulating the development of state support instruments such as feed-in tariffs. Next, attention is given on the introduction of energy storage systems in autonomous island grids. Such autonomous systems comprise ideal test-benches for energy storage and smart-grids, owed to the technical challenges they present on the one hand (e.g. low levels of energy diversity and limitations in terms of grid balancing capacity) and the high electricity production cost determining the local energy sector on the other (due to the need for oil imports). To this end, combined operation of RES with energy storage could, under the assumption of appreciable RES potential, prove cost-effective in comparison with the current solution of expensive, oil-based thermal power generation. Moreover, by considering the limited balancing capacity of such autonomous grids, which dictates the oversizing of the storage components in order to achieve increased energy autonomy, the trade-off between DSM and energy storage is next studied, becoming increasingly important as the quality of RES potential decays. With regards to utility-scale energy storage applications, the potential of bulk energy storage to support base-load RES contribution is investigated, proving in this way that the intermittent characteristics of RES power generation could be eliminated. This implies increased energy security at the level of national grids while also challenging the prospect of grid parity for such energy schemes. Furthermore, the market regulating capacity of utility-scale energy storage is reflected through the examination of different market-efficiency criteria, providing system operators with a valuable asset for the improved operation of electricity markets. Finally, the role of utility-scale energy storage in the optimum management of national electricity trade is investigated, designating the underlying problem of embodied carbon dioxide emissions’ exchange over cross-border transmission and paving the way for the consideration of energy storage aspects in electricity grid planning

Impact of demand-side management on the sizing of autonomous solar PV-based mini-grids

Solar PV-based autonomous mini-grids represent an economically affordable and robust electrification option for rural communities. However, the initial investment cost for renewable energy technologies such as solar PV remains high for rural communities. Implementation of demand-side management (DSM) could increase the cost-efficiency of mini-grids in rural areas. This requires demand-side knowledge, but little is still known of electricity demands in recently electrified areas and, in particular, of how DSM implementation could impact mini-grids. The few studies available focus either on systems or on appliance levels while this study aims to determine cost-efficiency impacts of DSM implementation at a category level. A shifting strategy is applied based on classification into high priority loads and low priority loads. Autonomous rural mini-grid components sizing for four different load categories and load flexibility are carried out using particle swarm optimization. The results show that different load category combinations result in large variations in terms of possible levelized energy cost reductions and, thus, in terms of the cost-optimal sizing of the mini-grid components. The DSM implementation on the household and productive use categories have the largest capacity of reducing the levelized energy cost, by 45.8% and 20.7%, respectively, compared to the no demand-side management case