Zechun Hu

Decentralized Vehicle-to-Grid Control for Primary Frequency Regulation Considering Charging Demands

Vehicle-to-grid (V2G) control has the potential to provide frequency regulation service for power system operation from electric vehicles (EVs). In this paper, a decentralized V2G control (DVC) method is proposed for EVs to participate in primary frequency control considering charging demands from EV customers. When an EV customer wants to maintain the residual state of charge (SOC) of the EV battery, a V2G control strategy, called battery SOC holder (BSH), is performed to maintain the battery energy around the residual SOC along with adaptive frequency droop control. If the residual battery energy is not enough for next trip, the customer needs to charge the EV to higher SOC level. Then, a smart charging method, called charging with frequency regulation (CFR), is developed to achieve scheduled charging and provide frequency regulation at the same time. Simulations on a two-area interconnected power system with wind power integration have shown the effectiveness of the proposed method.

Optimal siting and sizing of electric vehicle charging stations

The development of electric vehicles cannot be separated from charging infrastructures. At present, the construction of electric vehicle charging stations faces the problems on siting and sizing. This paper introduces the optimization process of the sizing and siting of electric vehicle charging stations, defines variables to represent the charging demand; abstracts the structure of road network to model and simulate with graph theory; solves the problem with Cplex. The objective of the model is to minimize the integrated cost of charging stations and consumers. The calculation results, using the data of Stockholm, Sweden, show that the method can effectively reduce the construction and operation costs, and facilitate user charging.

Photovoltaic and solar power forecasting for smart grid energy management

Due to the challenge of climate and energy crisis, renewable energy generation including solar generation has experienced significant growth. Increasingly high penetration level of photovoltaic (PV) generation arises in smart grid. Solar power is intermittent and variable, as the solar source at the ground level is highly dependent on cloud cover variability, atmospheric aerosol levels, and other atmosphere parameters. The inherent variability of large-scale solar generation introduces significant challenges to smart grid energy management. Accurate forecasting of solar power/irradiance is critical to secure economic operation of the smart grid. This paper provides a comprehensive review of the theoretical forecasting methodologies for both solar resource and PV power. Applications of solar forecasting in energy management of smart grid are also investigated in detail.

Optimal Coordination of Plug-In Electric Vehicles in Power Grids With Cost-Benefit Analysis—Part I: Enabling Techniques

Plug-in electric vehicles (PEVs) appear to offer a promising option for mitigating greenhouse emission. However, uncoordinated PEV charging can weaken the reliability of power systems. The proper accommodation of PEVs in a power grid imposes many challenges on system planning and operations. This work aims to investigate optimal PEV coordination strategies with cost-benefit analysis. In Part I, we first present a new method to calculate the charging load of PEVs with a modified Latin hypercube sampling (LHS) method for handling the stochastic property of PEVs. We then propose a new two-stage optimization model to discover the optimal charging states of PEVs in a given day. Using this model, the peak load with charging load of PEVs is minimized in the first stage and the load fluctuation is minimized in the second-stage with peak load being fixed as the value obtained in the first stage. An algorithm based on linear mixed-integer programming is provided as a suitable solution method with fast computation. Finally, we present a new method to calculate the benefit and cost for a PEV charging and discharging coordination strategy from a social welfare approach. These methods are useful for developing PEV coordination strategies in power system planning and supporting PEV-related policy making.

Vehicle-to-Grid Control for Supplementary Frequency Regulation Considering Charging Demands

Electric vehicles (EVs) as distributed storage devices have the potential to provide frequency regulation services due to the fast adjustment of charging/discharging power. In our previous research, decentralized vehicle-to-grid (V2G) control methods for EVs were proposed to participate in primary frequency control. In this paper, our attention is on bringing a large number of EVs into the centralized supplementary frequency regulation (SFR) of interconnected power systems. An aggregator is the coordinator between EVs and the power system control center. The aggregator calculates the total frequency regulation capacity (FRC) and expected V2G (EV2G) power of EVs based on the data communicated between the aggregator and individual EVs or EV charging stations. With FRC and EV2G power, a V2G control strategy is proposed for the aggregator to dispatch regulation requirements to EVs and EV charging stations. In individual EV charging stations, the FRC is calculated on the basis of the V2G power at present time, and EV2G power is presented considering both frequency regulation and charging demands. Besides, V2G control strategies are developed to distribute regulation requirements to each EV. Simulations on an interconnected power grid based on a practical power grid in China have demonstrated the effectiveness of the proposed strategies.

Cost-Benefit Analyses of Active Distribution Network Management, Part I: Annual Benefit Analysis

With more and more renewable energy generation (REG) connections, busbar voltage violation and line overloading problems may occur for some parts of a distribution network. However, building new circuits to accommodate REG may have high monetary and environmental costs. This paper considers distribution automation as a supplementary scheme to traditional primary asset investments and analyzes the operational benefits from introducing an autonomous regional active network management system (AuRA-NMS) to a practical distribution system with rich renewable sources. The benefits are quantified in terms of optimal power flow control and investment deferral, and the resulting quantification will inform distribution network operators of the trade-offs between investment in the automation system and in the primary assets, thus helping them to make cost-effective investment decisions. Time-series-based simulation for over an entire year is implemented to calculate the benefits of active power loss and curtailment reductions for AuRA-NMS over the current practice. Part I of this paper illustrates the current schemes for voltage control and constraint management, advanced voltage control and constraint management enabled by the distribution automation, and the annual benefit by introducing the AuRA-NMS to the system with different considerable new DG integrations. Part II analyzes the investment deferral benefit by deploying AuRA-NMS.

Optimal Coordination of Plug-in Electric Vehicles in Power Grids With Cost-Benefit Analysis—Part II: A Case Study in China

Continuing with a set of enabling techniques for the optimal coordination of plug-in electric vehicles (PEVs) in Part I, we present a case study in this paper using techniques based on the data collected in the Beijing-Tianjin-Tangshan Region (BTTR) China to discover optimal PEV coordination strategies and assess the attractiveness of these strategies. In Part II, we first present the charging characteristics for different categories of PEVs in BTTR and predict the optimal seasonal daily loads with PEVs under different PEV penetration levels using a two-stage optimization model in both 2020 and 2030. The simulation results indicate that optimal PEV coordination effectively reduces the peak load and smooths the load curve. Finally, we present a cost-benefit analysis of optimal coordination strategies by taking a social welfare approach. The analysis shows that the optimal coordination strategies are beneficial in terms of the reduction in capital investment in power grid expansion and that the attractiveness of a coordination strategy is related to the coordination level. The results also show that the fully coordinated charging and vehicle to grid are not the most attractive strategies. This case study is useful for better understanding the costs and benefits of PEV coordination strategies and for supporting PEV-related decision and policy making from a power system planning perspective.

Forecasting charging load of plug-in electric vehicles in China

In this paper, in order to forecast the charging load of plug-in electric vehicles (PEVs) in China in 2015, 2020, 2030, the development status and trends of PEVs in China is introduced first. Then the energy supply modes of different kinds of PEVs in China are analyzed. Correspondingly, the charging load model is proposed based on the charging needs of different kinds of cars. For forecasting the charging load, the charging periods are determined according to the probability distribution. With the charging methods (either on slow, regular, or fast mode), together with the starting point for state of charge (SOC) and charging needs of different PEV types, the actual charging time can be calculated. Accordingly, the range of starting charging time is narrowed. The Monte Carlo simulation method is then applied to determine the initial charging point based on probability distributions of starting charging time. The results indicate that the charging of EVs will pose significant impacts on the power grid in 2030 in China. The huge difference between charging peak and off-peak provides a substantial potential to coordinate the charging of EVs.

Lyapunov-Based Decentralized Excitation Control for Global Asymptotic Stability and Voltage Regulation of Multi-Machine Power Systems

This paper proposes a novel Lyapunov-based excitation control (LEC) technique to deal with both global asymptotic stability and voltage regulation for the multi-machine power systems. Lyapunov function is built as a quadratic form of the control objectives consisted of active power offset, rotor speed offset and terminal voltage offset. A completely controllable linear system is constructed to design the trajectories of the time-derivatives of the control objectives. Furthermore, time-derivative of Lyapunov function (TLF) is also expressed as a quadratic form of the control objectives. Feedback gains are chosen to guarantee the negative definition of the TLF for any real number except for the equilibrium point. Therefore, the global asymptotic stability is achieved. The design flexibility of the proposed method provides convenience to introduce the voltage feedback signal for maintaining acceptable voltage level. The system voltage is forced to converge to its reference accompanying with the energy attenuation of Lyapunov function. As a result, voltage deviation is eliminated when Lyapunov function is equal to zero. Finally, a Lyapunov-based decentralized excitation controller is developed for the multi-machine power systems, and it is only related to local measurements. Simulations on a six-machine power system have illustrated better performances in comparison to the existing controllers.

A Hierarchical Framework for Coordinated Charging of Plug-In Electric Vehicles in China

Plug-in electric vehicle (PEV) technology has drawn increasing amounts of attention in the last decade. As the worlds largest automotive market, China has recently made the electrification of transportation central to its national strategic plan. Because of the unique nature of the vertically regulated power industry, Chinas massive deployment of PEVs has to face unique challenges that may not be encountered by any other country/region. Therefore, a comprehensive coordinated PEV charging scheme is urgently needed to facilitate the smooth grid integration of PEVs at all levels (e.g., transmission systems, distribution systems, and charging stations). This paper presents detailed mathematical modeling of a novel hierarchical framework for coordinated PEV charging at multiple timescales (i.e., day-ahead and real-time). The proposed three-level (e.g., provincial level, municipal level, and charging station level) PEV charging strategy jointly optimizes system load profile and charging costs while satisfying customer charging requirements. The interrelationships between various levels in terms of energy transaction and information exchange are clearly identified. Case studies on Guangdong Province, China, are carried out and simulation results demonstrate the effectiveness of our proposed hierarchical control framework in reducing system peak demand and charging costs.