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With the increasing market penetration of electric vehicles (EVs), the charging behavior and driving characteristics of EVs have an increasing impact on the operation of power grids and traffic networks. Existing research on EV routing planning and charging navigation strategies mainly focuses on vehicle-road-network interactions, but the vehicle-to-vehicle interaction has rarely been considered, particularly in studying simultaneous charging requests. To investigate the interaction of multiple vehicles in routing planning and charging, a routing optimization of EVs for charging with an event-driven pricing strategy is proposed. The urban area of a city is taken as a case for numerical simulation, which demonstrates that the proposed strategy can not only alleviate the long-time queuing for EV fast charging but also improve the utilization rate of charging infrastructures. Note to Practitioners—This article was inspired by the concerns of difficulties for electric vehicle (EV)’s fast charging and the imbalance of the utilization rate of charging facilities. Existing route optimization and charging navigation research are mainly applicable to static traffic networks, which cannot dynamically adjust driving routes and charging strategies with real-time traffic information. Besides, the mutual impact between vehicles is rarely considered in these works in routing planning. To resolve the shortcomings of existing models, a receding-horizon-based strategy that can be applied to dynamic traffic networks is proposed. In this article, various factors that the user is concerned about within the course of driving are converted into driving costs, through which each road section of traffic networks is assigned the corresponding values. Combined with the graph theory analysis method, the mathematical form of the dynamic traffic network is presented. Then, the article carefully plans and adjusts EV driving routes and charging strategies. Numerical results demonstrate that the proposed method can significantly increase the adoption of EV fast charging while alleviating unreasonable distributions of regional charging demand. [ABSTRACT FROM AUTHOR]

Due to the increasing realisation of improving the utility of energy and reducing pollutant emissions, the electric vehicle has been a hot topic in electrical engineering courses. However, it is the scale evolution of electric vehicles that is the basis for investigating their impacts on the power grid. This paper presents the main steps of designing an educational tool based on system dynamic approach to understanding the electric vehicles evolution and arouses their interests in the course named Electric Vehicle and Smart Grid. This tool is a work done by a team of students based on theory and survey, calculating the size of electric vehicles. The effectiveness of this tool is verified by the case studies in this paper, including the scale evolution, analysing the influence factors and stimulating students' interests. In addition, this tool has been used in teaching to demonstrate the scale evolution intuitively, thus achieving better teaching. [ABSTRACT FROM AUTHOR]

The active distribution network is a new solution to the flexible utilization of distributed energy resources to suit the characteristics of the distribution network. Advanced “active” network management is to coordinate “generation, network, load” optimization and achieve the right balance between operational expenditure (OPEX) and capital expenditure (CAPEX). To demonstrate the advancement from introducing an active distribution network, the key features of distribution network planning mainly including traditional models is first introduced. Extensive literature in generic planning is then summarized and categorized in terms of objective functions, system modeling, solution algorithms, and tools. This is followed by an extended review and in-depth discussion of concepts and representative topic developments in optimal active distribution network planning. In contrast to traditional planning, it takes into account the effects from a range of active network interventions that are exercised at differing time scales while capturing the intrinsically stochastic behavior of renewable generation or demand response to produce strategic plans that are robust against a highly uncertain energy future. Finally, a multi-dimensional framework for optimal active distribution network planning is proposed to overcome the limitations of the current state of the art, and the challenges in each stage are also highlighted. [ABSTRACT FROM AUTHOR]

In this article, the impacts of alternative generation integration in a power grid are discussed from the view of complex network theory. Using the improved complex network index, the structural performance of the system could be assessed in planning. Also, the distribution of load and generation are also considered in the modeling. Compared with the existing planning method, the proposed method can not only solve alternative generation units siting issues but also locate the corresponding conventional generation to be curtailed or replaced. Furthermore, as more information is obtained,e.g., related policy or cost parameters, a multi-objective comprehensive decision model is designed, the weight coefficient of which is determined by the two-tuple linguistic decision method. The proposed indices and models can effectively realize fast location and help improve the structural performance of the system with appropriate alternative generation integration. The models and methods are tested and verified by test cases. [ABSTRACT FROM PUBLISHER]

A novel method for optimal sizing of energy storage system (ESS) in active distribution networks using state of energy (SOE) function is proposed in this letter. The SOE of ESS in an operational cycle is characterized by an approximately continuous function based on Fourier–Legendre series expansion. Then, the ESS capacity can be determined by the optimized SOE function extreme. The effectiveness and advantages of the proposed method are verified by test cases. [ABSTRACT FROM PUBLISHER]

Electric vehicles (EVs) have received significant attention in recent years. The high penetration of EVs increased the charging load in the distribution network, which has an enormous impact on "transportation and power grid" coupled energy networks. This paper developed the models and methods to evaluate the capacity of electrical energy supply based on voltage stability in the worst charging case scenario, under the existing coupled network. An optimization method with transportation network constraints is proposed to find the worst charging case scenario. In addition, the mobility of EVs is considered to calculate the load margin and the maximum number of EVs charging that a given grid can support in the critical situation. The method and model are simulated by test cases, which provide a perspective for realizing the EVs integration capacity limitation in urban areas considering the coupling relationship between transportation and power grids. Finally, the impact of charging location and route choice in the voltage margin limitation is emphasized. • A model for generating the worst charging scenario is proposed. • A voltage stability analysis considering EVs' integration is proposed. • The transportation and power grid are coupled and modeled. • The allowable maximum number of EVs is calculated. [ABSTRACT FROM AUTHOR]

Network pricing is essential for electricity system operators to recover investment and operation costs from network users. Current pricing schemes are only for generation and demand that purely withdraws or injects power from/into the system. However, they cannot properly price energy storage (ES), which has the dual characteristics of injecting and withdrawing power. This paper develops a novel pricing scheme for ESs in distribution systems operated by customers to reflect their impact on network planning and operation. A novel charging and discharging methodology is designed for ESs to respond to time of use tariffs for maximising electricity cost savings. The long-term incremental cost for ES is designed based on future reinforcement horizon and short-term operation cost is quantified by system congestion. Then, a novel pricing scheme for ES is designed by integrating the two costs. The pricing signals can guide ES operation to benefit both distribution network operators and ES owners. The new methodology is demonstrated on a small system with an ES of different features and then on a practical Grid Supply Point (GSP) area. [ABSTRACT FROM AUTHOR]