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Driven by new regulations, new market structures, and new energy resources, the smart grid has been the trigger for profound changes in the way that electricity is generated, distributed, managed, and consumed. The smart grid has raised the traditional power grid by using a two-way electricity and information flow to create an advanced, automated power supply network. However, these pioneering smart grid technologies must grow to adapt to the demands of the current digital society. In today’s digital landscape, we can access feasible data and knowledge that were merely inconceivable. This Special Issue aims to address the landscape in which smart grids are progressing, due to the advent of pervasive technologies like the Internet of Things (IoT). It will be the advanced exploitation of the massive amounts of data generated from (low-cost) IoT sensors that will become the main driver to evolve the concept of the smart grid, currently focused on infrastructure, towards the digital energy network paradigm, focused on service. Furthermore, collective intelligence will improve the processes of decision making and empower citizens. Original manuscripts focusing on state-of-the-art IoT networking and communications, M2M communications, cyberphysical system architectures, big data analytics or cloud computing applied to digital energy platforms, including design methodologies and practical implementation aspects, are welcome.

energy management system --- n/a --- home energy management system --- nanogrids --- electric energy storage --- genetic algorithm --- voltage unbalance --- harmonics --- self-consumption --- prosumer --- power system reliability --- microgrid --- communication --- low-cost solutions --- distributed energy resources --- LoRa technology --- smart inverter --- direct load control --- distributed generation --- power quality --- mixed-integer linear programming --- PV monitoring --- islanded operation --- wireless --- frequency variations --- demand response

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The extended papers in this Special Issue cover the topics of smart energy, nuclear systems, and micro energy grids. In “Electrical Loads and Power Systems for the DEMO Nuclear Fusion Project” and “Energy Analysis for the Connection of the Nuclear Reactor DEMO to the European Electrical Grid”, the authors introduce a European DEMO project. In “Comparison and Design of Resonant Network Considering the Characteristics of a Plasma Generator” the authors present a theoretical analysis and experimental study on the resonant network of the power conditioning system (PCS). In “Techno-Economic Evaluation of Interconnected Nuclear-Renewable Micro Hybrid Energy Systems with Combined Heat and Power”, the authors conducted a sensitivity analysis to identify the impact of the different variables on the investigated systems. In “Fault Current Tracing and Identification via Machine Learning Considering Distributed Energy Resources in Distribution Networks”, the authors propose a current tracing method to model the single distribution feeder as several independent parallel connected virtual lines, with the result of tracing the detailed contribution of different current sources to the power line current. From the five extended papers, we observe that the SEGE is actively engaged in smart grid and green energy techniques. We hope that the readers enjoy this Special Issue.

Research & information: general --- Technology: general issues --- plasma generator --- LCL network --- LCCL network --- phase compensation --- ZVS control --- current tracing --- fault current --- distributed energy resources --- network model --- nuclear power plant --- renewable energy --- hybrid energy system --- combined heat and power --- nuclear fusion --- tokamak --- generation power plant --- power system --- electrical transmission grid --- balance of plant --- DEMO --- electric loads --- plasma --- power flow --- power supply --- power systems

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This book focuses on the recent development of forecasting and risk management techniques for electricity markets. In addition, we discuss research on new trading platforms and environments using blockchain-based peer-to-peer (P2P) markets and computer agents. The book consists of two parts. The first part is entitled “Forecasting and Risk Management Techniques” and contains five chapters related to weather and electricity derivatives, and load and price forecasting for supporting electricity trading. The second part is entitled “Peer-to-Peer (P2P) Electricity Trading System and Strategy” and contains the following five chapters related to the feasibility and enhancement of P2P energy trading from various aspects.

Technology: general issues --- History of engineering & technology --- electricity markets --- non-parametric regression --- minimum variance hedge --- spline basis functions --- cyclic cubic spline --- weather derivatives --- n/a --- distributed energy resources (DER) --- P2P energy trading --- cooperative mechanism --- renewable energy --- multi agent system --- blockchain --- cashflow management of electricity businesses --- electricity derivatives and forwards --- retailers and power producers --- solar power and thermal energy --- optimal hedging using nonparametric techniques --- empirical simulations --- peer-to-peer energy trading --- distributed energy resources --- microgrid --- digital grid --- bidding strategy --- electricity price --- electricity load --- electricity price forecasting --- wind energy --- day-ahead market --- intra-day market --- balancing power market --- peer to peer energy market --- hardware control --- demonstration experiment --- home energy management systems --- electric vehicles --- bidding agent --- electric vehicle --- functional autoregressive model --- functional principle component analysis --- vector autoregressive model --- functional final prediction error (FFPE) --- naive method --- P2P electricity market --- market maker --- liquidity --- price fluctuation --- artificial market simulation

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The analysis of power systems under various conditions represents one of the most important and complex tasks in electrical power engineering. Studies in this area are necessary to ensure that the reliability, efficiency, and stability of the power system is not adversely affected. This issue is devoted to reviews and applications of modern methods of signal processing used to analyze the operation of a power system and evaluate the performance of the system in all aspects. Smart grids as an emerging research field of the current decade is the focus of this issue. Monitoring capability with data integration, advanced analysis of support system control, enhanced power security and effective communication to meet the power demand, efficient energy consumption and minimum costs, and intelligent interaction between power-generating and -consuming devices depends on the selection and implementation of advanced signal analysis and processing techniques.

History of engineering & technology --- convolutional neural networks --- multi-headed CNN --- CNN-LSTM --- forecasting --- solar output --- sliding window --- renewable energy --- data mining --- cluster analysis --- power quality --- global power quality index --- electrical power network --- distributed generation --- mining industry --- ward algorithm --- different working conditions --- power supply restoration --- power supply outages --- failures --- time intervals --- obtaining information --- information recognition --- connection harmonization --- virtual power plant --- distributed energy resources --- energy storage systems --- grid codes --- power systems --- smart grids --- prosumer --- business model --- economic efficiency --- sensitivity analysis

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The synergy between artificial intelligence and power and energy systems is providing promising solutions to deal with the increasing complexity of the energy sector. Multi-agent systems, in particular, are widely used to simulate complex problems in the power and energy domain as they enable modeling dynamic environments and studying the interactions between the involved players. Multi-agent systems are suitable for dealing not only with problems related to the upper levels of the system, such as the transmission grid and wholesale electricity markets, but also to address challenges associated with the management of distributed generation, renewables, large-scale integration of electric vehicles, and consumption flexibility. Agent-based approaches are also being increasingly used for control and to combine simulation and emulation by enabling modeling of the details of buildings’ electrical devices, microgrids, and smart grid components. This book discusses and highlights the latest advances and trends in multi-agent energy systems simulation. The addressed application topics include the design, modeling, and simulation of electricity markets operation, the management and scheduling of energy resources, the definition of dynamic energy tariffs for consumption and electrical vehicles charging, the large-scale integration of variable renewable energy sources, and mitigation of the associated power network issues.

EV charging --- multi-agent system --- digital twin --- customer satisfaction indicator --- smart microgrid --- energy management system --- real-time optimization --- immune system algorithm --- economic dispatch --- energy consumption --- wireless sensor network --- cooperation --- collaboration --- ontology --- energy sector --- scoping review --- decision-aid --- distributed energy resources --- distribution system operator --- reactive power management --- uncertainty --- day-ahead market --- balancing market --- bilateral trading --- market design --- variable renewable energy --- agent-based simulation --- MATREM system --- congestion management --- dynamic tariff --- agent-based distribution networks --- demand response --- routing protocols --- performance parameters --- Wireless Sensor Network (WSN)