A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes (original) (raw)
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Sensors (Basel, Switzerland), 2020
Deployment of efficient and cost-effective parking lots is a known bottleneck for the electric vehicles (EVs) sector. A comprehensive solution incorporating the requirements of all key stakeholders is required. Taking up the challenge, we propose a real-time EV smart parking lot model to attain the following objectives: (a) maximize the smart parking lot revenue by accommodating maximum number of EVs and (b) minimize the cost of power consumption by participating in a demand response (DR) program offered by the utility since it is a tool to answer and handle the electric power usage requirements for charging the EV in the smart parking lot. With a view to achieving these objectives, a linear programming-based binary/cyclic (0/1) optimization technique is developed for the EV charge scheduling process. It is difficult to solve the problems of binary optimization in real-time given that the complexity of the problem increases with the increase in number of EV. We deploy a simplified c...
2008 IEEE Energy 2030 Conference, 2008
This paper proposes an intelligent method for scheduling usage of available energy storage capacity from plugin hybrid electric vehicles (PHEV) and electric vehicles (EV). The batteries on these vehicles can either provide power to the grid when parked, known as vehicle-to-grid (V2G) concept or take power from the grid to charge the batteries on the vehicles. A scalable parking lot model is developed with different parameters assigned to fleets of vehicles. The size of the parking lot is assumed to be large enough to accommodate the number of vehicles performing grid transactions. In order to figure out the appropriate charge and discharge times throughout the day, binary particle swarm optimization is applied. Price curves from the California ISO database are used in this study to have realistic price fluctuations. Finding optimal solutions that maximize profits to vehicle owners while satisfying system and vehicle owners' constraints is the objective of this study. Different fleets of vehicles are used to approximate varying customer base and demonstrate the scalability of parking lots for V2G. The results are compared for consistency and scalability. Discussions on how this technique can be applied to other grid issues such as peaking power are included at the end.
Journal of Energy Storage, 2019
Charging/discharging management of electric vehicles (EVs) and dispatch of intermittent renewable energies will be probably two significant issues in future distribution system operation and planning. In addition, intelligent parking lots (IPLs) are widely employed due to ever-increasing number of EVs. In this paper, a novel stochastic approach is proposed for charging/discharging management of EVs parked in IPLs where the electric vehicles are interacting with each other and the upstream grid operator. A newly developed model is presented for the intelligent parking lot with hydrogen storage system (HSS) consisting of fuel cell, electrolyzer, and hydrogen storage tank as well as load demand in which practical constraints are satisfied. The costs of operation related to distribution system, including the purchasing cost of energy from upstream grid and the cost of EVs charging in IPLs, are formulated as the most important objectives of the proposed optimization problem. Particle swarm optimization (PSO) algorithm as a fast and population-based technique was carried out in simulations. And, based on the obtained simulation results, all technical and financial objectives are achieved.
Optimal Resource Allocation and Charging Prices for Benefit Maximization in Smart PEV-Parking Lots
IEEE Transactions on Sustainable Energy, 2017
The emerging interest in deployment of plug-in electric vehicles (PEVs) in distribution networks represents a great challenge to both system planners and owners of PEV-parking lots. The owners of PEV-parking lots might be interested in maximizing their profit via installing charging units to supply the PEV demand. However, with stringent rules of network upgrades, installing these charging units would be very challenging. Network constraints could be relaxed via controlling the net demand through integrating distributed generation (DG) and/or storage units. This paper presents an optimization model for determining the optimal mix of solar-based DG and storage units, as well as the optimal charging prices for PEVs. The main objective is to maximize the benefit of the PEV-parking lot's owner without violating system constraints. Two cases are considered in this paper: uncoordinated and coordinated PEV demand. A novel mathematical model is further developed whereby the behavior of vehicles' drivers, in response to different charging prices, is considered in generating the energy consumption of PEVs.
International Journal of Electrical Power & Energy Systems, 2020
A widespread appeal of electric vehicles entails, among other elements, the provision of fast charging stations to reduce the range anxiety. We present a novel structure and operating mechanism for EV parking lots where, traditionally, parked vehicles were charged in level-1 or level-2 charging modes. Due to ubiquitous presence of these parking lots in all urban and residential areas, the proposed approach actually leads to creation of just as many fast charging stations each accommodating a modest number of fast charging vehicles in proportion to the base capacity of the parking lot. A three-stage scheduling framework based on stochastic programming and MPC is introduced, consisting of day-ahead, periodic real-time and intra-period real-time planning for joint scheduling task of inflexible loads, slow-and fast-charged vehicles. The comprehensive fast charge allocation algorithm incorporates V2V concept, M/G/∞ queuing theory and a resource priority stack based on Most Laxity First concept. By providing energy to EVs of different charging classes, the proposed model can be considered a unified approach to prevent or at least reduce the need for separate fast charging stations in urban areas. Comprehensive examples demonstrate the effectiveness of the proposed approach in handling charging load of different EV classes.
On the Fair-Efficient Charging Scheduling of Electric Vehicles in Parking Structures
2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021
This work examines the off-line electric vehicle (EV) scheduling problem for cloud-based parking operators, that a-priori accept parking reservations for EVs requesting charging services during their stay. Specifically, it examines the fair EV charging scheduling problem, where fairness refers to the achievable charging levels of EVs contending for energy utilities within a planning horizon. For finding fair utility allocations the α-fairness approach is used, inspired by welfare economics, that is formulated as an integer linear program (ILP) and as an ant colony optimization (ACO), considering both the system's and EV owners' constraints and requirements. It is shown that with this approach the operator is able to control the fairness-efficiency trade-off (with system efficiency affecting the operator's revenue) by appropriately selecting the inequality aversion parameter α to best meet targeted performance metrics. Further, it is shown that ACO, deriving near-optimal allocations, significantly outperforms the ILP-based algorithm in terms of processing time (up to 99%), thus it is a promising approach when optimal ILP allocations cannot be derived fast enough for a practical implementation.
2018 20th National Power Systems Conference (NPSC), 2018
The electrification of transport is seen as one of the main pathways to achieve significant reductions in CO2 emissions. However, there are some issues related to it like, a sudden increase in electricity demand, high charging cost in dynamic price market, attending user's priority in charging his/her vehicle and the premium to be levied for such priority. In this paper, an intelligent charging strategy for Plug-in Electric Vehicle(PEV) incorporating a unified grid-to-vehicle(G2V) and vehicle-to-grid(V2G) framework with users' priority is proposed for optimal integration of PEVs in the existing distribution system. The intelligent strategy with objective function considering minimization of total charging cost, with users' priority as well as without priority is developed to study the impact of PEV integration from economic and technical perspective. The proposed strategy is implemented on test bench case consisting of 5 similar PEVs in a parking station. The uncertain p...
IEEE Transactions on Sustainable Energy
Demand response (DR) programs offer tremendous opportunities to those who have concerns about the future of energy. Since the DR strategies facilitate new technologies to take part in the power systems, the idea of spreading of electric vehicles (EVs) attracts the researchers around the world. In this study, an optimal energy management strategy for EV parking lots considering peak load reduction (PLR) based DR programs is built in stochastic programming framework, denoted by EV parking lot energy management (EV-PLEM). The proposed EV-PLEM aims to maximize the load factor during the daily operation of an EV parking lot taking into account the uncertain behavior of EVs such as arrival and departure times together with the stochasticity of the remaining state-of-energy (SoE) of EVs when they reach the parking lot. A set of case studies is conducted to validate the effectiveness of the suggested EV-PLEM concept, and credible results and useful findings are reported for the cases in which the EV-PLEM is implemented. Index Terms-Energy management, EV parking lots, demand response, stochastic systems, user interfaces. NOMENCLATURE The abbreviations, sets and indices, parameters along with variables used in this study are alphabetically given in following tables. The others non-listed are explained where they first appear. TABLE I ABBREVIATIONS DR Demand response EV Electric vehicle GHG Greenhouse gas emissions LSE Load serving entity J.P.S. Catalão acknowledges the support by FEDER funds through
Journal of Energy Storage, 2021
A large share of greenhouse gases (GHGs) emissions is related to the transportation systems. These systems can be transformed into the clean transportation ones using the electric vehicles (EVs). Therefore, the power distribution grid (PDG) is required in the future sustainable cities to facilitate the integration of the EVs to these systems. In such systems, the operation problem of the power distribution grid operators (PDGOs) changes in the presence of electric vehicle parking lots (EVPLs). Although the different models are proposed for the operation problem of the PDGOs and parking lot (PL) owners (PLOs), the interaction among the PLOs in also needs new decisionmaking framework. Therefore, in this paper, an appropriate energy management model for the EVPL community is presented for the operational scheduling of several PLs which they trade energy with each other besides energy exchange with the PDGO to maximize their profits. This model is a mixed-integer linear programming (MILP) problem which is solved by stochastic programming and using a simple additive weighting (SAW) method. The model also compares with two common models consisting of: 1) the PLO only purchases energy from PDGO, and 2) the PLO purchases/sells energy from/to the PDGO. The results show that in the proposed model in this paper the PLOs gain more profit in comparison with the common models. The profit depends on EVs' uncertainties and several factors that is investigated through the sensitivity analysis.
York University, 2015
The last few decades have seen growing concerns about climate change caused by global warming, which is cause primarily by CO 2 emissions. Thus, the reduction of these emissions has become critically important. One of the effective methods for achieving this goal is to shift towards green electricity energy resources and green vehicles in transportation. For these reasons, the goal of the work presented in this thesis was to address the challenges associated with the planning of plug-in electric vehicles (PEVs) parking lots in combination with renewable energy sources (RES) and battery energy storage systems (BESS) in power distribution networks. This thesis introduces a new planning technique that aims to minimize the overall capital and operational costs, taking into consideration the operational aspects of distribution networks, such as 1) coordinated PEV charging, 2) smart inverter control of renewable distributed generation (DG) units, and 3) smart scheduling of BESS. Moreover, a new model for the PEV coordinated charging demand is introduced in this work. Due to the complexity of the proposed planning approach, a combination between metaheuristic technique and deterministic optimization techniques have been utilized to manage both the planning and operational aspects respectively.