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Increasing the shares of Renewable Energy Sources (RES) and Distributed Energy Resources (DER) is one of the most important levers in many countries to cope with the environmental, political, and economic challenges of future energy supply. The underlying research question of this thesis is whether Distributed Storage Systems (DSS) at the end consumer level can economically foster the integration of intermittent and non-dispatchable resources by providing demand-side flexibility.

load and price forecasting --- economic analysis --- batteries --- distributed storage systems --- demand response

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At present, the impact of distributed energy resources in the operation of power and energy systems is unquestionable at the distribution level, but also at the whole power system management level. Increased flexibility is required to accommodate intermittent distributed generation and electric vehicle charging. Demand response has already been proven to have a great potential to contribute to an increased system efficiency while bringing additional benefits, especially to the consumers. Distributed storage is also promising, e.g., when jointly used with the currently increasing use of photovoltaic panels. This book addresses the management of distributed energy resources. The focus includes methods and techniques to achieve an optimized operation, to aggregate the resources, namely, by virtual power players, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as a main drive for their efficient use.

autonomous operation --- energy management system --- stochastic programming --- co-generation --- Unit Commitment (UC) --- distributed system --- demand-side energy management --- virtual power plant --- Powell direction acceleration method --- average consensus algorithm (ACA) --- transmission line --- interval optimization --- renewable energy --- microgrids --- scheduling --- business model --- non-cooperative game (NCG) --- domestic energy management system --- time series --- energy trading --- decision-making under uncertainty --- Demand Response Unit Commitment (DRUC) --- real-time simulation --- distributed generation --- discrete wavelet transformer --- microgrid (MG) --- probabilistic programming --- optimal bidding --- ac/dc hybrid microgrid --- building energy flexibility --- storage --- uncertainty --- Cat Swarm Optimization (CSO) --- advance and retreat method --- multiplier method --- microgrid --- Demand Response (DR) --- electricity markets --- aggregators --- fault localization --- aggregator --- consensus algorithm --- black start --- microgrid operation --- local controller --- thermal comfort --- diffusion strategy --- optimal operation --- power system restoration (PSR) --- energy flexibility --- ARIMA --- pricing strategy --- clustering --- adaptive droop control --- multi-agent system (MAS) --- hierarchical game --- energy flexibility potential --- demand response

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This book represents the Special Issue of Energies, entitled “Demand-Response in Smart Buildings”, that was published in the section “Energy and Buildings”. This Special Issue is a collection of original scientific contributions and review papers that deal with smart buildings and communities. Demand response (DR) offers the capability to apply changes in the energy usage of consumers—from their normal consumption patterns—in response to changes in energy pricing over time. This leads to a lower energy demand during peak hours or during periods when an electricity grid’s reliability is put at risk. Therefore, demand response is a reduction in demand designed to reduce peak load or avoid system emergencies. Hence, demand response can be more cost-effective than adding generation capabilities to meet the peak and/or occasional demand spikes. The underlying objective of DR is to actively engage customers in modifying their consumption in response to pricing signals. Demand response is expected to increase energy market efficiency and the security of supply, which will ultimately benefit customers by way of options for managing their electricity costs leading to reduced environmental impact.

History of engineering & technology --- demand response --- artificial neural network --- power predictions --- energy management --- genetic algorithm --- optimisation --- microgrid --- smart grid --- requests time --- cloud computing --- response time --- processing time --- resource allocation --- fog computing --- energy resource --- energy security --- energy sources --- Slovakia --- energy flexibility --- retrofitting interventions --- residential consumption --- electrification in the built environment --- smart cities --- smart energy management --- India --- energy efficiency --- low-carbon mobility --- water-energy nexus

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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.

Research & information: general --- Technology: general issues --- industry 4.0 --- digitalization --- demand response --- HVAC control --- dynamic programming --- nonlinear optimization --- energy storage --- regulatory barriers --- storage policy --- market regulations --- SWOT analysis --- deep neural networks --- short-term load forecasting --- renewable energy --- sustainability --- island communities --- demand flexibility --- energy management --- optimization --- hydrogen economy --- cost analysis --- life cycle costing --- methane reforming --- water electrolysis --- centralised hydrogen production --- smart grids (intelligent networks) --- phasor machine learning --- binary logistic regression --- wireless network --- Sensors --- decentralized --- community energy management --- lithium-ion battery --- capacity prediction --- state of health estimation --- time–frequency image analysis --- continuous wavelet transform (CWT) --- two-stage optimization --- risk-based hybrid demand response --- uncertainties --- conditional value at risk --- improved multi-layer artificial bee colony algorithm --- interconnected power system --- cybersecurity --- FPID controller --- automatic intrusion mitigation unit --- Virtual Oscillator Control --- parameter tuning --- voltage-mode inverter --- microgrid

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This book covers applied research on smart energy systems, smart grids, smart energy homes, smart energy products and services, and the advanced applications thereof, in the context of demand response and grid interactions. In particular, this book is focused on interdisciplinary research results that combine technical, social, environmental, and economic aspects of smart energy systems and smart energy products. Moreover, several chapters are based on the evaluation of real life cases, energy pilots, prototypes of smart energy products, and end user surveys and interviews.

load duration curve --- n/a --- ancillary services --- electricity pricing --- renewable energy --- consumption patterns --- smart home technology --- self-consumption --- solar charging --- smart appliances --- spatial and temporal aggregation --- energy products and services --- solar mobility --- dynamic pricing --- frequency containment reserve --- heat pumps --- users --- FCR --- renewable energy transition --- privacy protection --- end-users --- self-sufficiency --- energy system analysis --- reliability --- photovoltaic systems --- stakeholders --- uncertainty --- smart grids --- flexibility --- prosumer --- demand shifting --- resonance instability --- energy management --- grid-connected inverter --- electricity market --- demand management --- smart metering --- photovoltaic --- aggregator --- smart product design --- internal attack --- pseudo-random function --- power quality --- power systems simulation --- demand response