Guiding the coordinated charging of electric vehicles can alleviate the load fluctuation of power systems within a local area caused by uncoordinated charging of electric vehicles and greatly reduce the cost of power system operation. This will become an inevitable development trend of future energy system transformation.引导电动汽车协同充电,可以缓解电动汽车充电不协调造成的局部电力系统负荷波动,大大降低电力系统运行成本。这将成为未来能源系统转型的必然发展趋势。
The vigorous development of electric vehicles (EVs) can get rid of the environmental damage and dependence on petroleum resources caused by conventional petrol vehicles [1]. Without the guidance of basic policies or related regulations to guide the charging behavior of EV owners, the time and space required for charging EVs will be uncertain under the influence of seasonal and geographical factors [2]. Uncoordinated charging behavior can directly affect the magnitude of electric load fluctuations in local areas, increase the cost of power system operation [3], and reduce the utilization of fossil fuels.
The rapid development of wind and photovoltaic (PV) power generation on the supply side of the power system has become a common development trend worldwide. However, the energy supply side, whether wind or PV power generation technology, can be equally affected by seasonal and geographical factors, etc. Electricity supply has inherent characteristics, such as unstable supply, low energy density, and difficulty in accurate prediction. These uncertainties can put great pressure on the grid’s supply-side dispatching capabilities [4][5].
In the future, if we want to make the power system run smoothly and realize the steady transition of energy production methods from traditional thermal power generation to wind and PV power generation, we must solve the above two kinds of uncertainties. One is the uncertainty of the charging time on the electricity consumption side, and the other is the uncertainty of the power generation capacity on the generation side affected by environmental factors. In essence, it is to solve the mismatch between the supply and demand time of the two, which can improve energy utilization and reduce power storage and transportation costs [6].
Vehicle-to-grid (V2G) is the inevitable trend of low-carbon energy transition and the key to solving the above two problems. The current research focuses on unidirectional V2G, i.e., coordinated charging mode. Unidirectional scheduling of EVs’ charging to consume excess power can help the grid shave peaks and fill valleys, achieving a win-win situation.
The demand-side energy management strategies include pricing approaches [7]. Specifically, the aggregators or EV owners can shift their load according to the announced electricity price mechanism designed by the utility grid, and the total load curves can then be regulated accordingly [8][9]. The application of time-of-use (TOU) charging pricing to guide EV owners’ charging behavior in the world is mostly at the stage of static TOU prices [8][10]. In China, for example, most of the current urban residential electricity consumption is charged by sectional tiered prices. The industrial sector divides prices by seasons and fixed hours, dividing different periods of different seasons into peak hours, flat hours, and valley hours. However, it cannot respond quickly to the problem of load fluctuations in the power system due to the weather-related effects of renewable energy generation.
To address the above issues, this study designed a mobile application for cell phones. This application was designed to match the fluctuating load curve of the renewable energy generation system by guiding the charging behavior of EV owners through real-time fluctuating price changes. This means that the renewable energy generation power signal is converted into a price signal in real-time to provide EV owners, guiding them to assist in peak and valley reduction of the power system.
The application connects the beginning of the data stream to the power plant, which outputs the electricity price every two hours based on the weather and the amount of electricity generated. It is published on the application platform as quickly as possible to achieve a real-time presentation of the electricity price for the users. At the same time, the power plant can also give a price forecast based on the forecast weather conditions of the coming week, allowing consumers to choose their future charging times. This format satisfies the new charging model of the electricity system.
该应用程序将数据流的开头连接到发电厂,发电厂根据天气和发电量每两小时输出一次电价。它以最快的速度发布在应用平台上,以实现用户电价的实时呈现。同时,电厂还可以根据未来一周的天气预报情况给出价格预测,让消费者选择未来的充电时间。这种格式满足了电力系统的新充电模式。The effectiveness of coordinating the charging time of EVs through a price mechanism, thus reducing the load on the power system, has achieved a consensus in most research-based papers [11]. However, multiple research theories exist on specific price-setting methodologies.
目前主流收费定价的方法包括动态定价和静态TOU定价[12]。动态定价主要通过聚合器收集电动汽车的充电信息和电网的负载功率来构建计算电价的算法模型,还包括车主的充电需求习惯[13,14]。一些常见的算法模型是内点法[15],粒子群优化(PSO)算法[16,17]和遗传算法。电网通过实时功率变化定价方案[18]间接协调所有电动汽车的充电行为,以最大限度地降低充电成本。此外,需要单向通信网络来确保价格信息可以广播给电动汽车车主[13]。TOU充电模式通过将充电时间从高峰负荷期转移到谷负荷期来减少电动汽车车主的电费[19,20,21]。收费价格仅取决于时间,其范围和相应期限根据消费者行为和通过TOU定价实现的目标预先确定[22]。从电网负荷管理的角度,Ma等[23]构建了优化的费率模型,表明TOU价格在降低成本和拉平电网负荷曲线方面表现出很大的优势。区域TOU价格模型可以有效降低客户的收费成本,缓解峰谷负载差异和网络损耗[24]。Current methods of mainstream charging price setting include dynamic pricing and static TOU pricing [12]. Dynamic pricing mainly constructs an algorithm model to calculate the electricity price by collecting the charging information of EVs and the load power of the grid with an aggregator, also including the charging demand habits of vehicle owners [13][14]. Some of the common algorithmic models are the interior point method [15], the particle swarm optimization (PSO) algorithm [16][17], and the genetic algorithm. The grid indirectly coordinates the charging behavior of all EVs through a real-time power variation pricing scheme [18] to minimize the charging cost. Furthermore, a unidirectional communication network is necessary to ensure the price information can be broadcast to EV owners [13]. TOU charging models reduce EV owners’ electricity bills by shifting charging times from peak load periods to valley load periods [19][20][21]. The charging price depends on time only, and its range and corresponding period are predetermined according to consumer behavior and the objectives to be achieved through TOU pricing [22]. From the perspective of grid load management, Ma et al. [23] constructed an optimized rates model and showed that TOU prices show great advantages in reducing costs and flattening the grid load curve. The regional TOU price model can effectively reduce the charging cost of customers and mitigate peak-valley load differences and network losses [24].
The charging demand of EVs will increase the peak load of the power grid [25], and their large-scale uncoordinated charging will put enormous pressure on the power supply, thus affecting the safety and stability of the whole power system. To solve this problem, it is necessary to optimize the charging of large EVs [26]. From a technical point of view, the V2G scheme is an important transformation path [27]. In V2G, the aggregated power from a group of EVs can be used to support the grid by providing regulation services (to stabilize voltage and frequency) or reserve services (to meet sudden increases in demand or generator set outages). V2G modes can be divided into bidirectional V2G and unidirectional V2G. Bidirectional V2G means that while conventional charging piles supply power to the car, the EV power battery is also regarded as a decentralized energy storage unit of the power system. Reasonable utilization of EVs’ battery energy to achieve reverse power supply will alleviate the load shock of the grid. Thus, the EV is not only a movable load, but also a distributed energy source. This mode can be used to provide services such as frequency regulation or peak shaving of power grids [12]. However, due to technical and cost problems, it has not been possible to promote it on a large scale for the time being.
Unidirectional V2G is used to guide EVs to coordinated charging by cooperating with the grid operation rules. There are no reserve services. What’s more, the unidirectional V2G services can help consume the abundant renewable energy sources, such as solar and wind energy, by the coordinated charging strategy [28]. Unidirectional V2G can reduce power consumption during peak hours, improve power utilization during valley hours, and alleviate the impact of random charging demand on the grid [5]. Although the unidirectional V2G services still face some obstacles, solutions have been in process. Additionally, unidirectional V2G would build a solid foundation to implement bidirectional V2G in the future [28].
单向V2G通过配合电网运行规则,引导电动汽车协同充电。没有储备服务。更重要的是,单向V2G服务可以通过协调充电策略帮助消耗丰富的可再生能源,如太阳能和风能[28]。单向V2G可以降低高峰时段的功耗,提高低谷时段的电力利用率,减轻随机充电需求对电网的影响[5]。尽管单向V2G服务仍面临一些障碍,但解决方案一直在进行中。此外,单向V2G将为未来实施双向V2G奠定坚实的基础[28]。