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This book explores how the concepts, methods and tools of systemic analyses have been utilised in various contexts, and at different levels, to improve the efficiency and optimisation of sustainable energy systems.
Research & information: general --- renewable portfolio standards --- emissions trading scheme --- optimal operational strategy --- generation expansion plan --- energy planning --- public institution --- passive energy --- CRITIC method --- urban metabolism --- household energy metabolism --- household energy metabolism assessment methods --- household energy consumption --- energy systems optimisation --- exergy analysis --- cumulative-exergy consumption minimisation --- multi-energy systems --- energy-system design --- municipal energy systems --- internet of things --- IoT applications --- energy efficiency --- energy in buildings --- smart energy systems --- smart grid --- flexible demand --- energy storage --- concentrating solar power --- geographic information systems --- potential assessment --- renewable energy --- solar thermal --- South Africa --- CSP --- energy and economy transition --- decision making --- international energy security risk index --- multiple regression analysis --- multicollinearity test --- multicollinearity test with variance inflation factors --- renewable energy systems --- microgrids --- optimal expansion planning --- energy resilience --- resilient energy systems --- critical loads --- electric vehicles --- techno-economic analysis --- HOMER Pro --- New Zealand
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This book explores how the concepts, methods and tools of systemic analyses have been utilised in various contexts, and at different levels, to improve the efficiency and optimisation of sustainable energy systems.
Research & information: general --- renewable portfolio standards --- emissions trading scheme --- optimal operational strategy --- generation expansion plan --- energy planning --- public institution --- passive energy --- CRITIC method --- urban metabolism --- household energy metabolism --- household energy metabolism assessment methods --- household energy consumption --- energy systems optimisation --- exergy analysis --- cumulative-exergy consumption minimisation --- multi-energy systems --- energy-system design --- municipal energy systems --- internet of things --- IoT applications --- energy efficiency --- energy in buildings --- smart energy systems --- smart grid --- flexible demand --- energy storage --- concentrating solar power --- geographic information systems --- potential assessment --- renewable energy --- solar thermal --- South Africa --- CSP --- energy and economy transition --- decision making --- international energy security risk index --- multiple regression analysis --- multicollinearity test --- multicollinearity test with variance inflation factors --- renewable energy systems --- microgrids --- optimal expansion planning --- energy resilience --- resilient energy systems --- critical loads --- electric vehicles --- techno-economic analysis --- HOMER Pro --- New Zealand
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This book explores how the concepts, methods and tools of systemic analyses have been utilised in various contexts, and at different levels, to improve the efficiency and optimisation of sustainable energy systems.
renewable portfolio standards --- emissions trading scheme --- optimal operational strategy --- generation expansion plan --- energy planning --- public institution --- passive energy --- CRITIC method --- urban metabolism --- household energy metabolism --- household energy metabolism assessment methods --- household energy consumption --- energy systems optimisation --- exergy analysis --- cumulative-exergy consumption minimisation --- multi-energy systems --- energy-system design --- municipal energy systems --- internet of things --- IoT applications --- energy efficiency --- energy in buildings --- smart energy systems --- smart grid --- flexible demand --- energy storage --- concentrating solar power --- geographic information systems --- potential assessment --- renewable energy --- solar thermal --- South Africa --- CSP --- energy and economy transition --- decision making --- international energy security risk index --- multiple regression analysis --- multicollinearity test --- multicollinearity test with variance inflation factors --- renewable energy systems --- microgrids --- optimal expansion planning --- energy resilience --- resilient energy systems --- critical loads --- electric vehicles --- techno-economic analysis --- HOMER Pro --- New Zealand
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Buildings are one of the main causes of the emission of greenhouse gases in the world. Europe alone is responsible for more than 30% of emissions, or about 900 million tons of CO2 per year. Heating and air conditioning are the main cause of greenhouse gas emissions in buildings. Most buildings currently in use were built with poor energy efficiency criteria or, depending on the country and the date of construction, none at all. Therefore, regardless of whether construction regulations are becoming stricter, the real challenge nowadays is the energy rehabilitation of existing buildings. It is currently a priority to reduce (or, ideally, eliminate) the waste of energy in buildings and, at the same time, supply the necessary energy through renewable sources. The first can be achieved by improving the architectural design, construction methods, and materials used, as well as the efficiency of the facilities and systems; the second can be achieved through the integration of renewable energy (wind, solar, geothermal, etc.) in buildings. In any case, regardless of whether the energy used is renewable or not, the efficiency must always be taken into account. The most profitable and clean energy is that which is not consumed.
artificial neural network --- thermal performance --- dynamic simulation --- building renovation --- zero energy building --- building --- energy productivity --- building sector --- three-phase unbalance minimization --- optimization --- seasonal performance factor (SPF) --- envelope transmittance --- demolition --- envelope airtightness --- building energy prediction --- energy --- Korean household energy consumption --- floor envelope design --- building refurbishment --- perturbation and observation --- glazing --- ground and water source heat pump (ASHP --- sensitivity --- energy efficiency promotion --- model predictive control --- renovation --- home energy management system --- energy tunnel --- performance parameter design --- air --- coefficient of performance (COP) --- Arab region --- building rehabilitation --- ground heat transfer --- residential buildings --- Deutsche Gesellschaft für Nachhaltiges Bauen (DGNB) --- policy design --- building user activity --- Leadership in Energy & --- lightweight expanded clay aggregate (LECA) --- energy renovation --- energy performance --- urban modelling --- Maghreb --- analytical hierarchy process --- surface cooling --- thermal insulation --- Level(s) --- subtropical climate --- energy efficiency --- green building rating systems --- Ipomoea batatas --- big data --- life cycle cost analysis --- domestic hot water (DHW) --- multi-family buildings --- greenhouse --- building energy --- passive architecture --- prediction --- Haute Qualité Environnementale (HQE) --- Minimum-Energy Building (MEB) --- energy modeling --- Mashreq --- simulation engines --- HVAC demand --- test method --- adjustable step size --- life cycle cost --- energy saving ratio --- Environmental Design (LEED) --- influencing factors --- GSHP and WSHP) --- energy use --- subtropical climate building --- single-person household --- heat load --- energy performance standard --- technology package --- energy-performance gap --- GCC --- Building Research Establishment Assessment Method (BREEAM) --- energy pile --- nearly zero energy building --- co-simulation --- new construction --- space heating --- building stock energy demand --- low power loss --- maximum power point tracking --- envelope thermography --- extensive green roof --- OPERA-MILP
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This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
Technology: general issues --- History of engineering & technology --- Energy industries & utilities --- virtual power plant (VPP) --- power quality (PQ) --- global index --- distributed energy resources (DER) --- energy storage systems (ESS) --- power systems --- long-term assessment --- battery energy storage systems (BESS) --- smart grids --- conducted disturbances --- power quality --- supraharmonics --- 2–150 kHz --- Power Line Communications (PLC) --- intentional emission --- non-intentional emission --- mains signalling --- virtual power plant --- data mining --- clustering --- distributed energy resources --- energy storage systems --- short term conditions --- cluster analysis (CA) --- nonlinear loads --- harmonics, cancellation, and attenuation of harmonics --- waveform distortion --- THDi --- low-voltage networks --- optimization techniques --- different batteries --- off-grid microgrid --- integrated renewable energy system --- cluster analysis --- K-means --- agglomerative --- ANFIS --- fuzzy logic --- induction generator --- MPPT --- neural network --- renewable energy --- variable speed WECS --- wind energy conversion system --- wind energy --- frequency estimation --- spectrum interpolation --- power network disturbances --- COVID-19 --- time-varying reproduction number --- social distancing --- load profile --- demographic characteristic --- household energy consumption --- demand-side management --- energy management --- time series --- Hidden Markov Model --- short-term forecast --- sparse signal decomposition --- supervised dictionary learning --- dictionary impulsion --- singular value decomposition --- discrete cosine transform --- discrete Haar transform --- discrete wavelet transform --- transient stability assessment --- home energy management --- binary-coded genetic algorithms --- optimal power scheduling --- demand response --- Data Injection Attack --- machine learning --- critical infrastructure --- smart grid --- water treatment plant --- power system --- n/a --- 2-150 kHz
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This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
Technology: general issues --- History of engineering & technology --- Energy industries & utilities --- virtual power plant (VPP) --- power quality (PQ) --- global index --- distributed energy resources (DER) --- energy storage systems (ESS) --- power systems --- long-term assessment --- battery energy storage systems (BESS) --- smart grids --- conducted disturbances --- power quality --- supraharmonics --- 2–150 kHz --- Power Line Communications (PLC) --- intentional emission --- non-intentional emission --- mains signalling --- virtual power plant --- data mining --- clustering --- distributed energy resources --- energy storage systems --- short term conditions --- cluster analysis (CA) --- nonlinear loads --- harmonics, cancellation, and attenuation of harmonics --- waveform distortion --- THDi --- low-voltage networks --- optimization techniques --- different batteries --- off-grid microgrid --- integrated renewable energy system --- cluster analysis --- K-means --- agglomerative --- ANFIS --- fuzzy logic --- induction generator --- MPPT --- neural network --- renewable energy --- variable speed WECS --- wind energy conversion system --- wind energy --- frequency estimation --- spectrum interpolation --- power network disturbances --- COVID-19 --- time-varying reproduction number --- social distancing --- load profile --- demographic characteristic --- household energy consumption --- demand-side management --- energy management --- time series --- Hidden Markov Model --- short-term forecast --- sparse signal decomposition --- supervised dictionary learning --- dictionary impulsion --- singular value decomposition --- discrete cosine transform --- discrete Haar transform --- discrete wavelet transform --- transient stability assessment --- home energy management --- binary-coded genetic algorithms --- optimal power scheduling --- demand response --- Data Injection Attack --- machine learning --- critical infrastructure --- smart grid --- water treatment plant --- power system --- n/a --- 2-150 kHz
Choose an application
This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
virtual power plant (VPP) --- power quality (PQ) --- global index --- distributed energy resources (DER) --- energy storage systems (ESS) --- power systems --- long-term assessment --- battery energy storage systems (BESS) --- smart grids --- conducted disturbances --- power quality --- supraharmonics --- 2–150 kHz --- Power Line Communications (PLC) --- intentional emission --- non-intentional emission --- mains signalling --- virtual power plant --- data mining --- clustering --- distributed energy resources --- energy storage systems --- short term conditions --- cluster analysis (CA) --- nonlinear loads --- harmonics, cancellation, and attenuation of harmonics --- waveform distortion --- THDi --- low-voltage networks --- optimization techniques --- different batteries --- off-grid microgrid --- integrated renewable energy system --- cluster analysis --- K-means --- agglomerative --- ANFIS --- fuzzy logic --- induction generator --- MPPT --- neural network --- renewable energy --- variable speed WECS --- wind energy conversion system --- wind energy --- frequency estimation --- spectrum interpolation --- power network disturbances --- COVID-19 --- time-varying reproduction number --- social distancing --- load profile --- demographic characteristic --- household energy consumption --- demand-side management --- energy management --- time series --- Hidden Markov Model --- short-term forecast --- sparse signal decomposition --- supervised dictionary learning --- dictionary impulsion --- singular value decomposition --- discrete cosine transform --- discrete Haar transform --- discrete wavelet transform --- transient stability assessment --- home energy management --- binary-coded genetic algorithms --- optimal power scheduling --- demand response --- Data Injection Attack --- machine learning --- critical infrastructure --- smart grid --- water treatment plant --- power system --- n/a --- 2-150 kHz
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