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The present work deals with social welfare maximization for energy scheduling. The parties involved in this study are a utility company, a distribution system operator and residential end-users. It allows the different participants to share a common electrical grid, without violating network constraints. A smart grid, equipped with a two-way communication system on a district level, is considered. For this purpose, each participant exchanges information, in order to establish a power consumption schedule that optimizes its own objectives, within the grid constraints. This strategy is illustrated on a district level to avoid overloading the distribution network. The consumption profiles of end-users consist of background consumption; some end-users are equipped with a heat pump and/or an electric vehicle, each of which is capable of responding to price variations. The impact of several tariff structures on the stability of the grid is explored. First of all, flat and day/night tariff structures are considered, and it is shown that price variation provokes load synchronization and leads to network overloads. Next, a real-time pricing tariff structure is used. If each end-user optimizes its behaviour to minimize personal costs, the grid is unable to supply all power during peak moments. In conclusion, if power constraints are imposed, the same grid can be stabilized, even if power demands increase by a factor of three or four. In a final example, the impact of imbalance costs is examined. The cluster can be guided to maximize profits for the utility company from the imbalance mechanism. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A method to coordinate the charging of electric vehicles to avoid network congestion issues is proposed. The novelty is that the proposed method uses both the temporal as well as the locational flexibility of the electric vehicles for coordination. Based on the vehicle behavior information (trajectories, parking places and duration, etc...), the algorithm assures that all vehicles can follow their planned trajectories and that power constraints on each car park are always met. The proposed method, a price-based coordination method, is ran in a decentralized way. As a consequence the responsibility for constructing the charging schedules is put solely with the vehicle owners, and the charging location managers need only to be concerned with the network congestion issues. Simulation results for 1000 EV's and 132 parking locations are presented and discussed. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: We have explored to what extent charging electrical vehicles (EVs) can be exploited to stabilize smart grids. Firstly, we discuss the transition to a future with a lot of renewable energy resources. Next, a decentralized coordinated charging schedule for EVs is proposed, taking into account the comfort settings of the consumers and local and temporal flexibility. Based on the vehicle behavior information (trajectories, parking places and duration, etc.) the algorithm assures that all vehicles can follow their planned trajectories and that power constraints on each car park are always met. An advantage of this decentralized coordination algorithm is that the privacy of consumers, including their future trajectory planning, charging controllers, parking duration, etc. are all treated on local processors on board. As a consequence the responsibility for constructing the charging schedules is put only with the vehicle owner. On the other hand, the parking managers need only to be concerned with the network congestion issues. A first application focuses on controlling the power flows at these parking locations and on rescheduling the charging of the electrical vehicles, so that costs are minimized within the comfort settings and within the physical limitations of the charging stations. This coordinated charging is applied on a car fleet of 200 electrical vehicles and 56 parking locations. Trajectories are computed with an activity based model (FEATHERS). In a second application, the imbalance costs are taken into account as well. The main advantage is for the retailer, who can now actively use the flexibility of the charging process to lower his power trading costs. [Copyright &y& Elsevier]