Author: George S. Stavrakakis
Publisher: MDPI
ISBN: 303928374X
Category : Technology & Engineering
Languages : en
Pages : 182
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Book Description
Micro-power domestic organic Rankine cycle (ORC) systems and the selection of the expander and the working fluid are presented, analyzed thoroughly, and numerically evaluated. A promising decentralized hybrid PV-SOFC system is investigated for providing useful energy supply to commercial buildings, capable of power and heat generation at a lower cost. A hybrid solar-combined cycle power plant integrated with a packed-bed thermal energy storage system with a novel recycling configuration enables robust control of collector temperature and net power during times of high solar activity. An automated hybrid (solar and biomass) power plant for thermal energy production for indoor space heating loads coverage is presented. A comprehensive and up-to-date literature review is presented of non-iterative methods for the extraction of the single diode model parameters of photovoltaic modules. A prototype custom built two-speed gearbox with a single stage transmission electric vehicle achieves significant reductions in the overall energy consumption. Two new fuzzy models are presented of high concentrator photovoltaics using the high-accuracy Takagi–Sugeno–Kang approach and the ease of interpreting the Mamdani linguistic rules. Finally, the impact of plug-in hybrid electric vehicles (PHEVs) in the primary frequency regulation is studied and the effects of PHEVs in non-interconnected isolated power systems with significant renewable energy source (RES) penetration are demonstrated through simulations of the isolated power system of Cyprus Island.
Author: George S Stavrakakis
Publisher: Mdpi AG
ISBN: 9783036557113
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
An economic development model analyzes the adoption of alternative strategy capable of leveraging the economy, based essentially on RES. The combination of wind turbine, PV installation with new technology battery energy storage, DSM network and RES forecasting algorithms maximizes RES integration in isolated islands. An innovative model of power system (PS) imbalances is presented, which aims to capture various features of the stochastic behavior of imbalances and to reduce in average reserve requirements and PS risk. Deep learning techniques for medium-term wind speed and solar irradiance forecasting are presented, using for first time a specific cloud index. Scalability-replicability of the FLEXITRANSTORE technology innovations integrates hardware-software solutions in all areas of the transmission system and the wholesale markets, promoting increased RES. A deep learning and GIS approach are combined for the optimal positioning of wave energy converters. An innovative methodology to hybridize battery-based energy storage using supercapacitors for smoother power profile, a new control scheme and battery degradation mechanism and their economic viability are presented. An innovative module-level photovoltaic (PV) architecture in parallel configuration is introduced maximizing power extraction under partial shading. A new method for detecting demagnetization faults in axial flux permanent magnet synchronous wind generators is presented. The stochastic operating temperature (OT) optimization integrated with Markov Chain simulation ascertains a more accurate OT for guiding the coal gasification practice.
Author: George S. Stavrakakis
Publisher:
ISBN: 9783039283750
Category : Physics
Languages : en
Pages : 182
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Book Description
Micro-power domestic organic Rankine cycle (ORC) systems and the selection of the expander and the working fluid are presented, analyzed thoroughly, and numerically evaluated. A promising decentralized hybrid PV-SOFC system is investigated for providing useful energy supply to commercial buildings, capable of power and heat generation at a lower cost. A hybrid solar-combined cycle power plant integrated with a packed-bed thermal energy storage system with a novel recycling configuration enables robust control of collector temperature and net power during times of high solar activity. An automated hybrid (solar and biomass) power plant for thermal energy production for indoor space heating loads coverage is presented. A comprehensive and up-to-date literature review is presented of non-iterative methods for the extraction of the single diode model parameters of photovoltaic modules. A prototype custom built two-speed gearbox with a single stage transmission electric vehicle achieves significant reductions in the overall energy consumption. Two new fuzzy models are presented of high concentrator photovoltaics using the high-accuracy Takagi-Sugeno-Kang approach and the ease of interpreting the Mamdani linguistic rules. Finally, the impact of plug-in hybrid electric vehicles (PHEVs) in the primary frequency regulation is studied and the effects of PHEVs in non-interconnected isolated power systems with significant renewable energy source (RES) penetration are demonstrated through simulations of the isolated power system of Cyprus Island.
Author: Kwok-Kei Simon Ng
Publisher: Open Dissertation Press
ISBN: 9781361315460
Category :
Languages : en
Pages :
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Book Description
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
Author: Hossam Gabbar
Publisher: Academic Press
ISBN: 0128092327
Category : Technology & Engineering
Languages : en
Pages : 570
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Book Description
Smart Energy Grid Engineering provides in-depth detail on the various important engineering challenges of smart energy grid design and operation by focusing on advanced methods and practices for designing different components and their integration within the grid. Governments around the world are investing heavily in smart energy grids to ensure optimum energy use and supply, enable better planning for outage responses and recovery, and facilitate the integration of heterogeneous technologies such as renewable energy systems, electrical vehicle networks, and smart homes around the grid. By looking at case studies and best practices that illustrate how to implement smart energy grid infrastructures and analyze the technical details involved in tackling emerging challenges, this valuable reference considers the important engineering aspects of design and implementation, energy generation, utilization and energy conservation, intelligent control and monitoring data analysis security, and asset integrity. Includes detailed support to integrate systems for smart grid infrastructures Features global case studies outlining design components and their integration within the grid Provides examples and best practices from industry that will assist in the migration to smart grids
Author: Bin Zhou
Publisher: Frontiers Media SA
ISBN: 2832513255
Category : Technology & Engineering
Languages : en
Pages : 1092
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Book Description
Author: Behnam Mohammadi-ivatloo
Publisher: Springer
ISBN: 3030042960
Category : Technology & Engineering
Languages : en
Pages : 315
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Book Description
This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.
Author: Weihao Hu
Publisher: Frontiers Media SA
ISBN: 2832502806
Category : Technology & Engineering
Languages : en
Pages : 265
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Book Description
Author: Ning Zhang
Publisher: CRC Press
ISBN: 042984770X
Category : Technology & Engineering
Languages : en
Pages : 372
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Book Description
The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration.The first part presents mathematical theories of stochastic mathematics; the second presents modeling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation. It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.
Author: Bin Zhou
Publisher: Frontiers Media SA
ISBN: 2832536069
Category : Technology & Engineering
Languages : en
Pages : 329
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Book Description
