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Enabling Renewable Energy Energy Storage Demand Response And Energy Efficiency With A Community Based Master Controller Optimizer
Download Enabling Renewable Energy Energy Storage Demand Response And Energy Efficiency With A Community Based Master Controller Optimizer full books in PDF, epub, and Kindle. Read online Enabling Renewable Energy Energy Storage Demand Response And Energy Efficiency With A Community Based Master Controller Optimizer ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Enabling Renewable Energy, Energy Storage, Demand Response, and Energy Efficiency with a Community-based Master Controller-optimizer by : Byron Washom
Download or read book Enabling Renewable Energy, Energy Storage, Demand Response, and Energy Efficiency with a Community-based Master Controller-optimizer written by Byron Washom and published by . This book was released on 2013 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Annual Report by : California Energy Commission. Public Interest Energy Research
Download or read book Annual Report written by California Energy Commission. Public Interest Energy Research and published by . This book was released on 2009 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Control and Optimization of Distributed Energy Resources Using Dynamic Algorithms by : Trudie Wang
Download or read book Control and Optimization of Distributed Energy Resources Using Dynamic Algorithms written by Trudie Wang and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As concerns for the environment and energy independence leads a transition towards a power grid that depends increasingly on energy from renewable resources like solar and wind, the integration and intelligent control of distributed energy resources (DER) including photovoltaic (PV) arrays, controllable loads, energy storage (ES) and the batteries in plug-in electric vehicles (EVs) will be critical to realizing a power grid that can handle both the variability and unpredictability of renewable energy sources as well as increasing system complexity. In addition to providing added system reliability, DERs acting in coordination can be leveraged to address supply-demand imbalances through Demand Response (DR) and/or price signals on the electric power grid by enabling continuous bidirectional load balancing. Intelligent control and integration has the capability to reduce or shift demand peaks and improve grid efficiency by offsetting the need for spinning reserves and peaking power plants. In this dissertation, the use of dynamic and distributed algorithms that can handle the higher penetration of renewable resources in a more open and transparent energy market is explored. Specifically, we look at solving the power scheduling problem using Model Predictive Control (MPC) to ensure a dynamic response and the Alternating Direction Method of Multipliers (ADMM) to distribute the optimization problem when apropos. MPC allows the DERs to be adaptive and robust while ADMM encourages each DER to cooperate to achieve system-level goals while still operating and functioning independently. This enables policies and incentives to co-develop and work with optimization and control technologies to ensure a smooth transition to an infrastructure that can run on renewable energy resources and a more distributed grid. Climate change and ecological concerns coupled with economic concerns over fossil fuel prices are addressed not only through the integration of cleaner energy sources, but also by providing a way to encourage participation throughout the grid. Since the forthcoming grid will require integrating renewable energy at all different levels, we look specifically at an example of generation in a grid-connected PV system with storage as well as a distributed microgrid with onsite PV generation and demand response capabilities. We present simulation results that demonstrate the ability of the algorithms to respond dynamically to external price signals and provide benefits to the grid while respecting and maintaining the functional requirements of the local resources. Each example uses real data taken from measurements at generation and demand sites. While we focus on two of the more popular solutions currently being explored, the platforms using the algorithms are application agnostic in the sense that they can include a range of DERs with varying objectives. Since the algorithms used are both flexible and scalable, devices can be easily integrated as more come online. The platforms can also be implemented in remote areas and developing countries. In addition to demonstrating that such platforms can be implemented dynamically in real-time, the algorithms can also be used in models and simulations as a design tool to inexpensively develop future systems with more generation from renewable resources which can still operate efficiently and reliably.
Book Synopsis Flexible Load Control for Enhancing Renewable Power System Operation by : Yuanzheng Li
Download or read book Flexible Load Control for Enhancing Renewable Power System Operation written by Yuanzheng Li and published by Springer Nature. This book was released on with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Model Predictive Control Enabling Flexible Operation of Data Centers by : Tianyou Shao
Download or read book Model Predictive Control Enabling Flexible Operation of Data Centers written by Tianyou Shao and published by GRIN Verlag. This book was released on 2018-02-21 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2017 in the subject Engineering - Power Engineering, grade: 2.0, RWTH Aachen University (Institute for Automation of Complex Power Systems), language: English, abstract: To rise to the challenge of the growing number of distributed Renewable Energy Sources (RES) for grid integration, Ancillary Service (AS) is increasingly crucial to maintaining the stability of power grid worldwide. In recent years, discussions about Data Centers (DCs) no longer limit to their energy efficiency. Considering the rising rigid demand from ICT customer and the high energy demand of DC, it is possible for DC to be one of Demand Response (DR) resources providing ASs in the smart grid. This thesis presents an online energy-aware scheduling algorithm based on Model Predictive Control (MPC), which realizes a proper adjustment of DC power demand, enabling the flexible operation of DC. The present work focuses on the identification and implementation of an MPC strategy which aims at a proper scheduling for DC which makes the total power consumption of DC flexible to track the reference signal in a DR context. It is demonstrated how the combination and interaction of the components under DC architecture can be utilized to achieve the realizable potential of operational flexibility for AS. Numerical simulation results have been carried out aimed at the later application in real pilot DCs. Furthermore, the capacity of resisting disturbance of this MPC approach has been discussed.
Author :California Energy Commission. Energy Research and Development Division Publisher : ISBN 13 : Total Pages :122 pages Book Rating :4.:/5 (318 download)
Book Synopsis Natural Gas Research and Development ... Annual Report by : California Energy Commission. Energy Research and Development Division
Download or read book Natural Gas Research and Development ... Annual Report written by California Energy Commission. Energy Research and Development Division and published by . This book was released on 2013 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Recent Advances in Renewable Energy Automation and Energy Forecasting by : Sarat Kumar Sahoo
Download or read book Recent Advances in Renewable Energy Automation and Energy Forecasting written by Sarat Kumar Sahoo and published by Frontiers Media SA. This book was released on 2023-12-08 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advancement of sustainable energy is becoming an important concern for many countries. The traditional electrical grid supports only one-way interaction of power being delivered to the consumers. The emergence of improved sensors, actuators, and automation technologies has consequently improved the control, monitoring and communication techniques within the energy sector, including the Smart Grid system. With the support of the aforementioned modern technologies, the information flows in two-ways between the consumer and supplier. This data communication helps the supplier in overcoming challenges like integration of renewable technologies, management of energy demand, load automation and control. Renewable energy (RE) is intermittent in nature and therefore difficult to predict. The accurate RE forecasting is very essential to improve the power system operations. The forecasting models are based on complex function combinations that include seasonality, fluctuation, and dynamic nonlinearity. The advanced intelligent computing algorithms for forecasting should consider the proper parameter determinations for achieving optimization. For this we need, new generation research areas like Machine learning (ML), and Artificial Intelligence (AI) to enable the efficient integration of distributed and renewable generation at large scale and at all voltage levels. The modern research in the above areas will improve the efficiency, reliability and sustainability in the Smart grid.
Book Synopsis Integration of Clean and Sustainable Energy Resources and Storage in Multi-Generation Systems by : Farkhondeh Jabari
Download or read book Integration of Clean and Sustainable Energy Resources and Storage in Multi-Generation Systems written by Farkhondeh Jabari and published by Springer Nature. This book was released on 2020-07-09 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents design principles, performance assessment and robust optimization of different poly-generation systems using renewable energy sources and storage technologies. Uncertainties associated with demands or the intermittent nature of renewables are considered in decision making processes. Economic and environmental benefits of these systems in comparison with traditional fossil fuels based ones are also provided. Case studies, numerical results, discussions, and concluding remarks have been presented for each proposed system/strategy. This book is a useful tool for students, researchers, and engineers trying to design and evaluate different zero-energy and zero-emission stand-alone grids.
Book Synopsis Demand Response and Energy Storage for a Cost Optimal Residential Energy Supply with Renewable Generation by : Franziska Adamek
Download or read book Demand Response and Energy Storage for a Cost Optimal Residential Energy Supply with Renewable Generation written by Franziska Adamek and published by . This book was released on 2011 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modeling and Control of Static Converters for Hybrid Storage Systems by : Fekik, Arezki
Download or read book Modeling and Control of Static Converters for Hybrid Storage Systems written by Fekik, Arezki and published by IGI Global. This book was released on 2021-09-17 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The energy transition initiated in recent years has enabled the growing integration of renewable production into the energy mix. Microgrids make it possible to maximize the efficiency of energy transmission from source to consumer by bringing the latter together geographically and by reducing losses linked to transport. However, the lack of inertia and the micro-grid support system makes it weak, and energy storage is necessary to ensure its proper functioning. Current storage technologies do not make it possible to provide both a large capacity of energy and power at the same time. Hybrid storage is a solution that combines the advantages of several technologies and reduces their disadvantages. Modeling and Control of Static Converters for Hybrid Storage Systems covers the modeling, control theorems, and optimization techniques that solve many scientific problems for researchers in the field of power converter control for renewable energy hybrid storage and places particular emphasis on the modeling and control of static converters for hybrid storage systems. Covering topics ranging from energy storage to power generation, this book is ideal for automation engineers, electrical engineers, mechanical engineers, professionals, scientists, academicians, master's and doctoral students, and researchers in the disciplines of electrical and mechanical engineering.
Book Synopsis Market-based Demand Response Integration in Super-smart Grids in the Presence of Variable Renewable Generation by : Sahand Behboodi Kalhori
Download or read book Market-based Demand Response Integration in Super-smart Grids in the Presence of Variable Renewable Generation written by Sahand Behboodi Kalhori and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Variable generator output levels from renewable energies is an important technical obstacle to the transition from fossil fuels to renewable resources. Super grids and smart grids are among the most effective solutions to mitigate generation variability. In a super grid, electric utilities within an interconnected system can share generation and reserve units so that they can produce electricity at a lower overall cost. Smart grids, in particular demand response programs, enable flexible loads such as plug-in electric vehicles and HVAC systems to consume electricity preferntially in a grid-friendly way that assists the grid operator to maintain the power balance. These solutions, in conjunction with energy storage systems, can facilitate renewable integration.This study aims to provide an understanding of the achievable benefits from integrating demand response into wholesale and retail electricity markets, in particular in the presence of significant amounts of variable generation. Among the options for control methods for demand response, market-based approaches provide a relatively efficient use of load flexibility, without restricting consumers' autonomy or invading their privacy. In this regard, a model of demand response integration into bulk electric grids is presented to study the interaction between variable renewables and demand response in the double auction environment, on an hourly basis. The cost benefit analysis shows that there exists an upper limit of renewable integration, and that additional solutions such as super grids and/or energy storage systems are required to go beyond this threshold. The idea of operating an interconnection in an unified (centralized) manner is also explored. The traditional approach to the unit commitment problem is to determine the dispatch schedule of generation units to minimize the operation cost. However, in the presence of price-sensitive loads (market-based demand response), the maximization of economic surplus is a preferred objective to the minimization of cost. Accordingly, a surplus-maximizing hour-ahead scheduling problem is formulated, and is then tested on a system that represents a 20-area reduced model of the North America Western Interconnection for the planning year 2024. The simulation results show that the proposed scheduling method reduces the total operational costs substantially, taking advantage of renewable generation diversity.The value of demand response is more pronounced when ancillary services (e.g. real-time power balancing and voltage/frequency regulation) are also included along with basic temporal load shifting. Relating to this, a smart charging strategy for plug-in electric vehicles is developed that enables them to participate in a 5-minute retail electricity market. The cost reduction associated with implementation of this charging strategy is compared to uncontrolled charging. In addition, an optimal operation method for thermostatically controlled loads is developed that reduces energy costs and prevents grid congestion, while maintaining the room temperature in the comfort range set by the consumer. The proposed model also includes loads in the energy imbalance market. The simulation results show that market-based demand response can contribute to a significant cost saving at the sub-hourly level (e.g. HVAC optimal operation), but not at the super-hourly level. Therefore, we conclude that demand response programs and super grids are complementary approaches to overcoming renewable generation variation across a range of temporal and spatial scales.
Book Synopsis Resilient Control Architectures and Power Systems by : Craig Rieger
Download or read book Resilient Control Architectures and Power Systems written by Craig Rieger and published by John Wiley & Sons. This book was released on 2022-01-26 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the fundamentals of resilient power grid control applications with this up-to-date resource from four industry leaders Resilient Control Architectures and Power Systems delivers a unique perspective on the singular challenges presented by increasing automation in society. In particular, the book focuses on the difficulties presented by the increased automation of the power grid. The authors provide a simulation of this real-life system, offering an accurate and comprehensive picture of a how a power control system works and, even more importantly, how it can fail. The editors invite various experts in the field to describe how and why power systems fail due to cyber security threats, human error, and complex interdependencies. They also discuss promising new concepts researchers are exploring that promise to make these control systems much more resilient to threats of all kinds. Finally, resilience fundamentals and applications are also investigated to allow the reader to apply measures that ensure adequate operation in complex control systems. Among a variety of other foundational and advanced topics, you'll learn about: The fundamentals of power grid infrastructure, including grid architecture, control system architecture, and communication architecture The disciplinary fundamentals of control theory, human-system interfaces, and cyber security The fundamentals of resilience, including the basis of resilience, its definition, and benchmarks, as well as cross-architecture metrics and considerations The application of resilience concepts, including cyber security challenges, control challenges, and human challenges A discussion of research challenges facing professionals in this field today Perfect for research students and practitioners in fields concerned with increasing power grid automation, Resilient Control Architectures and Power Systems also has a place on the bookshelves of members of the Control Systems Society, the Systems, Man and Cybernetics Society, the Computer Society, the Power and Energy Society, and similar organizations.
Book Synopsis Data Driven Artificial Intelligence Techniques in Renewable Energy System by : Ke Ning
Download or read book Data Driven Artificial Intelligence Techniques in Renewable Energy System written by Ke Ning and published by . This book was released on 2021 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today's power grid is composed of different kinds of distributed energy resources (DER) such as solar panels, wind farms, batteries and power transformers. DERs often come with data interfaces and IoT sensors which generate large amounts of data. Besides monitoring device status, those data can be utilized to improve system efficiency and generate additional values. My thesis is to examine the benefits of technologies that incorporate AI algorithms on the growing DER data in a technical perspective; First, a new field after IoT technology, called AIoT (Artificial Intelligence Internet of Things) is introduced, which are new technologies combining artificial intelligence (AI) and IoT to each other and creating new opportunities in the distributed energy resources (DER) field. Second, the thesis focuses on three areas of AIoT applications (1) fault prediction in photovoltaic system and power transformers; (2) remaining useful life (RUL) prediction of IoT enabled equipment; (3) AI-enabled algorithms can automate processes and make real time grid system optimization, such as energy storage, demand response (DR) and grid flexibility. The main focus is on data driven AI techniques that differentiate from traditional statistics or knowledge-based systems, present algorithm applicability, compare improvement over traditional method and business value created in each area. Finally, in the smart grid concept, all AIoT powered distributed energy resources (DER) can be aggregated in terms of virtual power plant (VPP), which enable the management of efficient and reliable power network on a large scale, and coordinate demand and supply in real-time. The AI enabled VPP architecture is presented, which utilized all the AIoT technologies and can provide valuable system capacity, flexibility and reliability.
Book Synopsis Energy Management System for Dispatchable Renewable Power Generation by : Amer Al-Hinai
Download or read book Energy Management System for Dispatchable Renewable Power Generation written by Amer Al-Hinai and published by CRC Press. This book was released on 2022-11-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enhancing the integration of renewable power generation from wind and solar into the traditional power network requires the mitigation of the vulnerabilities affecting the grid as a result of the intermittent nature of these resources. Variability and ramp events in power output are the key challenges to the system operators due to their impact on system balancing, reserves management, scheduling, and commitment of generation units. This book presents development of energy management system for renewable power generation (EMSRPG) tool that aims to achieve power-dispatching strategies based on forecasting renewable energy resources outputs to guarantee optimal dispatch of hybrid wind-solar photovoltaic power systems (HWSPS). The key selling points of the book include the following: Renewable energy management in modern and future smart power systems Energy management systems Modeling and simulations using a real-time digital simulator (RTDS) High penetration level of renewable energy sources Case studies based on Oman’s power systems and other power grids This book discusses the challenges of integrating renewable resources, including low inertia systems, hosting capacity limitations of existing power systems, and weak grids. It further examines the detailed topologies, operation principles, recent developments in control techniques, and stability of power systems with a large scale of renewables. Finally, it presents case studies of recent projects from around the world where dispatchable power plant techniques are used to enhance power system operation.
Book Synopsis Flexible Load Control for Enhancing Renewable Power System Operation by : Yuanzheng Li
Download or read book Flexible Load Control for Enhancing Renewable Power System Operation written by Yuanzheng Li and published by Springer. This book was released on 2024-07-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the pressing challenges faced by renewable power system operation (RPSO) due to the increasing penetration of renewable energy and flexible load. These challenges can be divided into two categories. Firstly, the inherent uncertainties associated with renewable energy sources pose significant difficulties in RPSO. Secondly, the presence of various types of flexible load, along with their complex constraint relationships, adds to the operational complexities. Recognizing the growing emphasis on the economic and low-carbon aspects of RPSO, this book focuses on the key issues of flexible load control. It mainly consists of following categories: (1) The control of data centers, a booming flexible load, to enhance RPSO through renewable energy integration and advanced robust multi-objective optimization. (2) The introduction of flexible industrial load control, employing effective demand-supply cooperative responding strategies for RPSO. (3) The exploration of electric vehicle flexible charging load control and centralized electric vehicle charging system control in the context of RPSO. The book also covers the emerging field of flexible integrated load control for renewable energy-based comprehensive energy system operation. Aimed at researchers, engineers, and graduate students in electrical engineering and computer science, this book provides a valuable resource for understanding and implementing flexible load control in the context of RPSO.
Book Synopsis Power Electronics-Enabled Autonomous Power Systems by : Qing-Chang Zhong
Download or read book Power Electronics-Enabled Autonomous Power Systems written by Qing-Chang Zhong and published by John Wiley & Sons. This book was released on 2020-06-08 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power systems worldwide are going through a paradigm shift from centralized generation to distributed generation. This book presents the SYNDEM (i.e., synchronized and democratized) grid architecture and its technical routes to harmonize the integration of renewable energy sources, electric vehicles, storage systems, and flexible loads, with the synchronization mechanism of synchronous machines, to enable autonomous operation of power systems, and to promote energy freedom. This is a game changer for the grid. It is the sort of breakthrough — like the touch screen in smart phones — that helps to push an industry from one era to the next, as reported by Keith Schneider, a New York Times correspondent since 1982. This book contains an introductory chapter and additional 24 chapters in five parts: Theoretical Framework, First-Generation VSM (virtual synchronous machines), Second-Generation VSM, Third-Generation VSM, and Case Studies. Most of the chapters include experimental results. As the first book of its kind for power electronics-enabled autonomous power systems, it • introduces a holistic architecture applicable to both large and small power systems, including aircraft power systems, ship power systems, microgrids, and supergrids • provides latest research to address the unprecedented challenges faced by power systems and to enhance grid stability, reliability, security, resiliency, and sustainability • demonstrates how future power systems achieve harmonious interaction, prevent local faults from cascading into wide-area blackouts, and operate autonomously with minimized cyber-attacks • highlights the significance of the SYNDEM concept for power systems and beyond Power Electronics-Enabled Autonomous Power Systems is an excellent book for researchers, engineers, and students involved in energy and power systems, electrical and control engineering, and power electronics. The SYNDEM theoretical framework chapter is also suitable for policy makers, legislators, entrepreneurs, commissioners of utility commissions, energy and environmental agency staff, utility personnel, investors, consultants, and attorneys.
Book Synopsis Optimal Planning and Management of Stochastic Demand and Renewable Energy in Smart Power Grid by : Kwok-Kei Simon Ng
Download or read book Optimal Planning and Management of Stochastic Demand and Renewable Energy in Smart Power Grid written by Kwok-Kei Simon Ng and published by Open Dissertation Press. This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Optimal Planning and Management of Stochastic Demand and Renewable Energy in Smart Power Grid" by Kwok-kei, Simon, Ng, 吳國基, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: To combat global climate change, the reduction of carbon emissions in different industries, particularly the power industry, has been gradually moving towards a low-carbon profile to alleviate any irreversible damage to the planet and our future generations. Traditional fossil-fuel-based generation is slowly replaced by more renewable energy generation while it can be harnessed. However, renewables such as solar and wind are stochastic in nature and difficult to predict accurately. With the increasing content of renewables, there is also an increasing challenge to the planning and operation of the grid. With the rapid deployment of smart meters and advanced metering infrastructure (AMI), an emerging approach is to schedule controllable end-use devices to improve energy efficiency. Real-time pricing signals combined with this approach can potentially deliver more economic and environmental advantages compared with the existing common flat tariffs. Motivated by this, the thesis presents an automatic and optimal load scheduling framework to help balance intermittent renewables via the demand side. A bi-level consumer-utility optimization model is proposed to take marginal price signals and wind power into account. The impact of wind uncertainty is formulated in three different ways, namely deterministic value, scenario analysis, and cumulative distributions function, to provide a comprehensive modeling of unpredictable wind energy. To solve the problem in off-the-shelf optimization software, the proposed non-linear bi-level model is converted into an equivalent single-level mixed integer linear programming problem using the Karush-Kuhn-Tucker optimality conditions and linearization techniques. Numerical examples show that the proposed model is able to achieve the dual goals of minimizing the consumer payment as well as improving system conditions. The ultimate goal of this work is to provide a tool for utilities to consider the demand response model into their market-clearing procedure. As high penetration of distributed renewable energy resources are most likely applied to remote or stand-alone systems, planning such systems with uncertainties in both generation and demand sides is needed. As such, a three-level probabilistic sizing methodology is developed to obtain a practical sizing result for a stand-alone photovoltaic (PV) system. The first-level consists of three modules: 1) load demand, 2) renewable resources, and 3) system components, which comprise the fundamental elements of sizing the system. The second-level consists of various models, such as a Markov chain solar radiation model and a stochastic load simulator. The third-level combines reliability indices with an annualized cost of system to form a new objective function, which can simultaneously consider both system cost and reliability based on a chronological Monte Carlo simulation and particle swamp optimization approach. The simulation results are then tested and verified in a smart grid laboratory at the University of Hong Kong to demonstrate the feasibility of the proposed model. In summary, this thesis has developed a comprehensive framework of demand response on variable end-use consumptions with stochastic generation from renewables while optimizing both reliability and cost. Smart grid technologies, such as renewables, microgrid, storage, load signature, and demand
