There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.

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A Review of Smart Cities Based on the Internet of Things Concept

Smart grid has modernized the way electricity is generated, transported, distributed, and consumed by integrating advanced sensing, communications, and control in the day-to-day operation of the grid. Electricity is a core utility for the functioning of society and for the services provided by information and communication technologies (ICTs). Several concepts of the smart grid, such as dynamic pricing, distributed generation, and demand management, have significantly impacted the operation of ICT services, in particular, communication networks and data centers. Ongoing energy-efficiency and operational expenditures reduction efforts in communication networks and data centers have gained another dimension with those smart grid concepts. In this paper, we provide a comprehensive survey on the smart grid-driven approaches in energy-efficient communications and data centers, and the interaction between smart grid and information and communication infrastructures. Although the studies on smart grid, energy-efficient communications, and green data centers have been separately surveyed in previous studies, to this end, research that falls in the intersection of those fields has not been properly classified and surveyed yet. We start our survey by providing background information on the smart grid and continue with surveying smart grid-driven approaches in energy-efficient communication systems, followed by energy, cost and emission minimizing approaches in data centers, and the corresponding cloud network infrastructure. We discuss the open issues in smart grid-driven approaches in ICTs and point some important research directions such as the distributed renewable energy generation capability-coupled communication infrastructures, optimum energy-efficient network design for the smart grid environment, the impact of green communication techniques on the reliability and latency requirements of smart grid data, workload consolidation with smart grid-awareness, and many more.

Energy-Efficient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues

Plug-in electric vehicles (PEV) are emerging as an efficient and sustainable alternative for private and public road transportation. From the point of view of electric grids, PEVs are currently considered as simple loads due to their low market penetration. However, as the PEV fleet grows, implementation of an intelligent management system will be necessary in order to avoid large capital expenditures in network reinforcements and negative effects on electric distribution networks, such as: voltage deviations, transformers and lines saturations, increase of electrical losses, etc. These issues may jeopardize the safety and reliability of the grid. As a consequence, this topic has been researched in many papers where a wide range of solutions have been proposed. This paper presents a review of different strategies, algorithms and methods to implement a smart charging control system. Also significant projects around the world about PEVs integration are presented. Finally, on the basis of this review, main findings and some recommendations are presented.

Plug-in electric vehicles in electric distribution networks: A review of smart charging approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy-management mechanism for the smart grid that enables each prosumer (i.e., an energy consumer who also produces electricity) of the network to participate in energy trading with other prosumers and the grid. This poses a significant challenge in terms of modeling the decisionmaking process of the participants' conflicting interests and motivating prosumers to participate in energy trading and cooperate, if necessary, in achieving different energy-management goals. Therefore, such a decisionmaking process needs to be built on solid mathematical and signal processing principles that can ensure an efficient operation of the electric power grid. This article provides an overview of the use of game-theoretic approaches for P2P energy trading as a feasible and effective means of energy management. Various game- and auction-theoretic approaches are discussed by following a systematic classification to provide information on the importance of game theory for smart energy research. This article also focuses on the key features of P2P energy trading and gives an introduction to an existing P2P testbed. Furthermore, the article gives specific game- and auction-theoretic models that have recently been used in P2P energy trading and discusses important findings arising from these approaches.

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Transforming Energy Networks via Peer-to-Peer Energy Trading: The Potential of Game-Theoretic Approaches

In this paper, we propose a novel demand side management technique to reduce the peak load of the system. We consider a smart power system with distributed users that request their energy demands to an energy provider and the energy provider dynamically updates the energy prices based on the load profiles of the users. The users try to minimize the Peak-to-Average Ratio (PAR) of the power system by charging for their batteries at low-demand periods and discharging the energy at high-demand periods. We also propose a distributed demand side management algorithm using a game theoretical approach in which each user tries to minimize its total energy cost. In simulation results, we show that the proposed algorithm will simultaneously minimize the PAR and the total energy cost.

Demand side management to reduce Peak-to-Average Ratio using game theory in smart grid

Demand-side management, together with the integration of distributed energy storage have an essential role in the process of improving the efficiency and reliability of the power grid. In this paper, we consider a smart power system in which users are equipped with energy storage devices. Users will request their energy demands from an energy provider who determines their energy payments based on the load profiles of users. By scheduling the energy consumption and storage of users regulated by a central controller, the energy provider tries to minimize the square euclidean distance between the instantaneous energy demand and the average demand of the power system. The users intend to reduce their energy payment by jointly scheduling their appliances and controlling the charging and discharging process for their energy storage devices. We apply game theory to formulate the energy consumption and storage game for the distributed design, in which the players are the users and their strategies are the energy consumption schedules for appliances and storage devices. Based on the game theory setup and proximal decomposition, we also propose two distributed demand side management algorithms executed by users in which each user tries to minimize its energy payment, while still preserving the privacy of users as well as minimizing the amount of required signaling with the central controller. In simulation results, we show that the proposed algorithms provide optimality for both energy provider and users.

Distributed Demand Side Management with Energy Storage in Smart Grid

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or ‘users’). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

Optimal charging and discharging for multiple PHEVs with demand side management in vehicle-to-building

Due to the high levels of renewable integration into the future power system, matching supply to demand becomes much more challenging, which requires system operators to have sufficient ramping flexibility to respond to the huge demand-supply gap when renewable generation suddenly drops off. To overcome this challenge, microgrids have been advocated as a viable solution to reduce variability and uncertainty associated with renewable generation by rescheduling their energy generation and storage resources based on grid flexibility requirements. In this paper, we propose an incentive mechanism design to motivate microgrids to participate in the peak ramp minimization problem for the system. By offering reimbursement for each microgrid to deviate from the original optimal operation point, the ramping capability requirement to match supply demand can be significantly reduced. We model and analyze the economic interaction between the distribution system operator (DSO) and microgrids using the Nash bargaining theory. The Nash bargaining solution (NBS) can be obtained by solving the centralized social welfare maximization problem. However, due to the distributed topology of the power network as well as independent decision-making nature of microgrids, the centralized design is not suitable for practical implementation. Therefore, we propose two distributed algorithms to achieve the NBS using the alternating direction method of multipliers decomposition technique, which can execute in either synchronous fashion or asynchronous fashion. The simulation results demonstrate the convergence performance of the proposed distributed algorithms as well as the efficacy of our model in achieving benefits for both microgrids and the DSO.

Incentive Mechanism Design for Integrated Microgrids in Peak Ramp Minimization Problem

We consider a distributed reactive power compensation problem in a distribution network in which users locally generate reactive power using distributed generation units to contribute to the local voltage control. We model and analyze the interaction between one electric utility company and multiple users by using the Nash bargaining theory. On one hand, users determine the amount of active and reactive power generation for their distributed generation units. On the other hand, the electric utility company offers reimbursement for each user based on the amount of reactive power dispatched by that user. We first quantify the benefit for the electric utility company and users in the reactive power compensation problem. Then we derive the optimal solution for the active and reactive power generation, as well as reimbursement for each user under two different bargaining protocols, namely sequential bargaining and concurrent bargaining. Numerical results show that both the electric utility company and users benefit from the proposed decentralized reactive power compensation mechanism, and the overall system efficiency is improved.

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Hung Khanh Nguyen

Papers

Demand side management to reduce Peak-to-Average Ratio using game theory in smart grid

Distributed Demand Side Management with Energy Storage in Smart Grid

Optimal charging and discharging for multiple PHEVs with demand side management in vehicle-to-building

Incentive Mechanism Design for Integrated Microgrids in Peak Ramp Minimization Problem

Decentralized Reactive Power Compensation Using Nash Bargaining Solution