40 research outputs found

    Control of Energy Storage

    Get PDF
    Energy storage can provide numerous beneficial services and cost savings within the electricity grid, especially when facing future challenges like renewable and electric vehicle (EV) integration. Public bodies, private companies and individuals are deploying storage facilities for several purposes, including arbitrage, grid support, renewable generation, and demand-side management. Storage deployment can therefore yield benefits like reduced frequency fluctuation, better asset utilisation and more predictable power profiles. Such uses of energy storage can reduce the cost of energy, reduce the strain on the grid, reduce the environmental impact of energy use, and prepare the network for future challenges. This Special Issue of Energies explore the latest developments in the control of energy storage in support of the wider energy network, and focus on the control of storage rather than the storage technology itself

    Real-Time Control Framework for Active Distribution Networks Theoretical Definition and Experimental Validation

    Get PDF
    The great challenge of massively integrating the volatile distributed power-generation into the power system is strongly related to the evolution of their operation and control. The literature of the last decade has suggested two models for such an evolution: (i) the supergrid model, based on enhanced continental/intercontinental network interconnections (mainly DC) for bulk transmission, (ii) the microgrid mode, where small medium/low voltage networks interfacing heterogeneous resources, such as local generation, energy storage and active customers, are intelligently managed so that they are operated as independent cells capable of providing different services from each other and operate in islanded mode. Irrespective of the model that will eventually emerge, the control of heterogeneous distributed resources represents a fundamental challenge for both supergrid and microgrid models. This requires the definition of scalable and composable control methods that guarantee the optimal and feasible operation of distribution grids in order to satisfy local objectives (e.g., distribution grid power balance), as well as the provision of ancillary services to the external bulk transmission (e.g., primary and secondary frequency supports). Several control methodologies have been proposed to achieve these goals, and the majority of them have been inspired by the classic time-layered approach traditionally adopted in power systems that are associated with different time-scales and extension of the controlling area, i.e. primary, secondary and tertiary controls, ranging from sub-seconds to hours, respectively. In the context of microgrids, these three levels of control can be associated with a decision process that can be centralized (i.e., a dedicated central controller decides on the operation of the system resources) and/or decentralized (each element decides based on its own rules). In the current literature, the former is used for long-term, whereas the latter for short-term decisions. In particular, primary controls are typically deployed through fully decentralized schemes mainly relying on the use of droop control. With this in mind, in this thesis we propose, and experimentally validate, a novel control framework called COMMELEC â A Composable Framework for Real-Time Control of Active Distribution Networks, Using Explicit Power Set-Points. It controls a power grid in real-time based on a multi-agent structure, using a simple and low-bandwidth communication protocol. Such a framework enables a controller to easily steer an entire network as an equivalent energy resource, thus making an entire system able to provide grid support by exploiting the flexibility of its components in real-time. The main features of the framework are (i) that it is able to indirectly control the reserve of the storage systems, thus maximizing the autonomy of the islanding operation, (ii) that it keeps the system in feasible operation conditions and better explores, compared to traditional techniques, the various degrees of freedom that characterize the system, and (iii) that it maintains the system power-equilibrium without using the frequency as a global variable, even being able to do so in inertia-less systems. Our framework has been extensively validated, first by simulations but, more importantly, in a real-scale microgrid laboratory specially designed and setup for this goal. This is the first real-scale experiment that proves the applicability of a droop-less explicit power-flow control mechanism in microgrids

    Wind Energy Harvesting and Conversion Systems: A Technical Review

    Get PDF
    Wind energy harvesting for electricity generation has a significant role in overcoming the challenges involved with climate change and the energy resource implications involved with population growth and political unrest. Indeed, there has been significant growth in wind energy capacity worldwide with turbine capacity growing significantly over the last two decades. This confidence is echoed in the wind power market and global wind energy statistics. However, wind energy capture and utilisation has always been challenging. Appreciation of the wind as a resource makes for difficulties in modelling and the sensitivities of how the wind resource maps to energy production results in an energy harvesting opportunity. An opportunity that is dependent on different system parameters, namely the wind as a resource, technology and system synergies in realizing an optimal wind energy harvest. This paper presents a thorough review of the state of the art concerning the realization of optimal wind energy harvesting and utilisation. The wind energy resource and, more specifically, the influence of wind speed and wind energy resource forecasting are considered in conjunction with technological considerations and how system optimization can realise more effective operational efficiencies. Moreover, non-technological issues affecting wind energy harvesting are also considered. These include standards and regulatory implications with higher levels of grid integration and higher system non-synchronous penetration (SNSP). The review concludes that hybrid forecasting techniques enable a more accurate and predictable resource appreciation and that a hybrid power system that employs a multi-objective optimization approach is most suitable in achieving an optimal configuration for maximum energy harvesting

    Optimal Co-Design of Microgrids and Electric Vehicles: Synergies, Simplifications and the Effects of Uncertainty.

    Full text link
    The burgeoning electrification of automobiles is causing convergence of the transportation and electrical power systems. This is visible in localized micropower systems, or microgrids, that supply plug-in vehicles. Though each system is designed by a separate industry, the need to reduce petroleum use and greenhouse gas emissions directs us to study the interface between these systems and develop methods to design both systems simultaneously. A method is presented for optimal co-design of a microgrid and electric vehicles using a nested optimal dispatch problem to solve for the operation of the microgrid and vehicles. This nested structure is implemented within a sequential optimization and reliability analysis loop to solve for the desired system reliability given uncertainties in the power load and solar power supply. The method is demonstrated for the case of co-designing a military microgrid and its all-electric tactical vehicles. The co-design approach results in a combined system design that minimizes capital investment and operating costs while meeting the reliability and performance requirements of both systems. The electric vehicles are shown to increase system reliability by providing energy storage without compromising their driving performance, and this support is shown to be robust to changes in the vehicle plug-in scheduling. The resulting optimal designs are highly-dependent on the input parameters, such as fuel cost and cost of capital equipment. For scenarios with high fuel costs and low battery prices, the co-design systems diverges significantly from separately-designed systems, resulting in improved performance and lower total costs.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91403/1/johnjohn_1.pd

    Innovation in Energy Systems

    Get PDF
    It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field

    Future Smart Grid Systems

    Get PDF
    This book focuses on the analysis, design and implementation of future smart grid systems. This book contains eleven chapters, which were originally published after rigorous peer-review as a Special Issue in the International Journal of Energies (Basel). The chapters cover a range of work from authors across the globe and present both the state-of-the-art and emerging paradigms across a range of topics including sustainability planning, regulations and policy, estimation and situational awareness, energy forecasting, control and optimization and decentralisation. This book will be of interest to researchers, practitioners and scholars working in areas related to future smart grid systems

    Innovation in Energy Systems

    Get PDF
    It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field

    Model based forecasting for demand response strategies

    Get PDF
    The incremental deployment of decentralized renewable energy sources in the distribution grid is triggering a paradigm change for the power sector. This shift from a centralized structure with big power plants to a decentralized scenario of distributed energy resources, such as solar and wind, calls for a more active management of the distribution grid. Conventional distribution grids were passive systems, in which the power was flowing unidirectionally from upstream to downstream. Nowadays, and increasingly in the future, the penetration of distributed generation (DG), with its stochastic nature and lack of controllability, represents a major challenge for the stability of the network, especially at the distribution level. In particular, the power flow reversals produced by DG cause voltage excursions, which must be compensated. This poses an obstacle to the energy transition towards a more sustainable energy mix, which can however be mitigated by using a more active approach towards the control of the distribution networks. Demand side management (DSM) offers a possible solution to the problem, allowing to actively control the balance between generation, consumption and storage, close to the point of generation. An active energy management implies not only the capability to react promptly in case of disturbances, but also to ability to anticipate future events and take control actions accordingly. This is usually achieved through model predictive control (MPC), which requires a prediction of the future disturbances acting on the system. This thesis treat challenges of distributed DSM, with a particular focus on the case of a high penetration of PV power plants. The first subject of the thesis is the evaluation of the performance of models for forecasting and control with low computational requirements, of distributed electrical batteries. The proposed methods are compared by means of closed loop deterministic and stochastic MPC performance. The second subject of the thesis is the development of model based forecasting for PV power plants, and methods to estimate these models without the use of dedicated sensors. The third subject of the thesis concerns strategies for increasing forecasting accuracy when dealing with multiple signals linked by hierarchical relations. Hierarchical forecasting methods are introduced and a distributed algorithm for reconciling base forecasters is presented. At the same time, a new methodology for generating aggregate consistent probabilistic forecasts is proposed. This method can be applied to distributed stochastic DSM, in the presence of high penetration of rooftop installed PV systems. In this case, the forecasts' errors become mutually dependent, raising difficulties in the control problem due to the nontrivial summation of dependent random variables. The benefits of considering dependent forecasting errors over considering them as independent and uncorrelated, are investigated. The last part of the thesis concerns models for distributed energy markets, relying on hierarchical aggregators. To be effective, DSM requires a considerable amount of flexible load and storage to be controllable. This generates the need to be able to pool and coordinate several units, in order to reach a critical mass. In a real case scenario, flexible units will have different owners, who will have different and possibly conflicting interests. In order to recruit as much flexibility as possible, it is therefore importan

    A Framework For Microgrid Planning Using Multidisciplinary Design Optimization

    Get PDF
    Microgrids are local energy providers that can potentially reduce energy expenses and emissions by utilizing distributed energy resources (DERs) and are alternatives to existing centralized systems. This thesis investigates the optimal design and planning of such microgrids using a multidisciplinary design optimization approach based framework. Among a variety of DERs it is widely accepted that renewable resources of energy play an important role in providing a sustainable energy supply infrastructure, as they are both inexhaustible and nonpolluting. However the intermittent nature and the uncertainties associated with renewable technologies pose sufficient technological and economical challenges for system planners. Design of complex engineering systems has evolved into a multidisciplinary field of study. We develop a framework for design and planning of complex engineering systems under uncertainty using an approach of multidisciplinary design optimization under uncertainty (MDOUU). The framework has been designed to be general enough to be applicable to a large variety of complex engineering systems while it is simple to apply. MDOUU framework is a three stage planning strategy which allows the system planners to consider all aspects ranging from uncertainty in resources, technological feasibility, economics, and life cycle impacts of the system and choose an optimal design suited to their localized conditions. Motivation behind using MDOUU lies not only in the optimization of the individual systems or disciplines but also their interactions between each other. Following the modeling of the resources, a deterministic optimization model for planning microgirds is developed and results are evaluated using Monte Carlo simulations. Given the obvious limitations of the deterministic model in not being able to handle uncertainty efficiently and resulting in an expensive design we extended the model to a two stage stochastic programming model which provides a unified approach in determining the sizing of microgrids by considering uncertainty implicitly by means of scenarios. Probabilistic scenarios are developed using C-vine copulas that model nonlinear dependence. We evaluate the significance of the stochastic programming model using standardized metrics evaluating benefits of using the stochastic model. As any product or service needs to be evaluated for its environmental impacts, MDOUU provisions an LCA module that evaluates the environmental impacts and energy demands of the components of the system based on extensive literature and databases using openLCA as a tool. The overall system selection involves multiple criteria and interests of different stakeholders. This requires a multi-attribute decision system and a comprehensive ranking approach providing a list of possible configuration based on their relative importance as denoted by the stakeholders. We use Analytical Hierarchical Process (AHP) combined with compromise programming to rank a list of configurations based on economic and environmental attributes such as GHG emissions saved, cost of energy, annual energy production, net present value (NPV) etc. It allows the planners to make decisions considering the interests of a majority of stakeholders. The MDOUU framework proposed in this thesis with specific application to the microgrid planning problem contributes in helping the planners handle uncertainty of renewable resources of energy and environmental impacts in a systematic way. As such there is no method available in the literature which considers planning of microgrid using such holistic and multidisciplinary framework. The MDOUU framework is a generic tool and is useful for planning problems in a variety of complex systems
    corecore