5G network-based Internet of Things for demand response in smart grid: A survey on application potential

This paper proposes a distribution system restoration model which is in response to multiple outages caused by natural disasters. The proposed restoration model includes the coordination of routing repair crews (RRCs), mobile battery-carried vehicles (MBCVs), and networked microgrids (NMGs) formed by soft open points (SOPs). The travel and repair time constraints are modeled for each RRC; travel path and charging strategy are modeled for each MBCV; and the network reconfiguration is developed considering the optimal operation of SOP-based NMGs. The proposed model is presented as a mixed-integer linear program which is solved by an auxiliary induce function based algorithm to reduce the computational complexity. The modified IEEE 33-bus and 69-bus distribution systems are tested with multiple outages. The presented results demonstrate the effectiveness of the proposed model.

Multiperiod Distribution System Restoration With Routing Repair Crews, Mobile Electric Vehicles, and Soft-Open-Point Networked Microgrids

This paper focuses on the development of electric vehicle (EV) charging infrastructure in the UK, which is a vital part of the delivering ultra-low-emission vehicle (ULEV) and will transition into low emission energy systems in the near future. Following a brief introduction to global landscape of EV and its infrastructure, this paper presents the EV development in the UK. It then unveils the government policy in recent years, charging equipment protocols or standards, and existing EV charging facilities. Circuit topologies of charging infrastructure are reviewed. Next, three important factors to be considered in a typical site, i. e., design, location and cost, are discussed in detail. Furthermore, the management and operation of charging infrastructure including different types of business models are summarized. Last but not least, challenges and future trends are discussed.

/pdf/a-review-on-electric-vehicle-charging-infrastructure-afklrci0wr.pdf

A Review on Electric Vehicle Charging Infrastructure Development in the UK

A charging pricing strategy of electric vehicle fast charging stations for the voltage control of electricity distribution networks

Demand response (DR) has been widely recognized as an important approach to balance the power grid and reduce peak load of power systems. In order to better estimate the capability and the expense of peak load reduction through DR, we need to obtain the residential load profile and customers’ attitudes toward DR programs. Based on a large-scale online survey collected among over 1500 customers from New York and Texas in the U.S., this paper investigates the relationships among household appliance activities (e.g., electric water heater and air conditioner), load profiles, and incentive-based DR (IBDR) participation for peak load curtailment through reward payment. The daily load profiles of major home appliances are developed. Additionally, this paper estimates the expense of reducing the yearly peak of the local grid load. Finally, this paper addresses the importance of investigating the multifaceted factors of affecting IBDR participation and provides useful suggestions to utility companies when implementing DR programs.

Estimating the Profile of Incentive-Based Demand Response (IBDR) by Integrating Technical Models and Social-Behavioral Factors

Renewable energy based distributed generation (DG) has the potential to reach high penetration levels in the residential region. However, its integration at the demand side will cause rapid power fluctuations of the tie-line in the residential region. The traditional generators are generally difficult to manage rapid power fluctuations due to their insufficient efficiency requirements and low responding speed. With an effective control strategy, the demand side resources (DSRs) including DGs, electric vehicles and thermostatically-controlled loads at the demand side, are able to serve as the energy storage system to smooth the load fluctuations. However, it is a challenge to properly model different types of DSRs. To solve this problem, a unified state model is first developed to describe the characteristics of different DSRs. Then a load curve smoothing strategy is proposed to offset the load fluctuations of the tie-line of the residential region, where a control matrix deduced from the unified state model is introduced to manage the power outputs of different DSRs, considering the response order and the comfort levels. Finally, a residential region with households is used to validate the load curve smoothing strategy based on the unified state model, and the results show that the power fluctuation rate of the tie-line is significantly decreased. Meanwhile, comparative study results are shown to demonstrate the advantages of the unified state model based load curve smoothing strategy.

/pdf/load-curve-smoothing-strategy-based-on-unified-state-model-2upelmurwh.pdf

Load curve smoothing strategy based on unified state model of different demand side resources

The penetration of the distributed photovoltaic (PV) has caused inevitable power fluctuations in the distribution network The traditional generators can hardly respond to the rapid load power fluctuations With the development of the vehicle-to-grid (V2G) technology, the aggregated electric vehicles (EVs) are able to operate as an energy storage system (ESS) to follow the rapid power fluctuations Thus it is critical to obtain the maximum energy storage capacity of aggregated EVs and propose an effective smoothing control strategy for the coordinated power control of EVs when responding to the power fluctuations To solve this problem, based on the maximum operation area of an individual EV considering the travelling behaviors, the response parameters of the aggregated EVs, such as the total exchanged power, the response capacity of the total exchanged power, the energy storage capacity and the SOC value, are defined to describe the energy storage characteristics of the aggregated EVs Then a load power smoothing control strategy is proposed to smooth the load power fluctuations of the distribution network The required power change is determined by evaluating the power fluctuation rate of the load, and then the required power change is allocated to each EV based on a developed SOC-adaptive method The simulation results show that the aggregated EVs are able to decrease power fluctuation rate of the load and the travelling comfort levels of EV users are guaranteed with the SOC-adaptive method

Load power smoothing control of distribution network including photovoltaic generation with energy storage from electric vehicles

In order to fully take advantage of the available reactive power from EV chargers (EVCs), a volt-var optimal control (VVOC) strategy for power system integrated with wind farms is proposed. The VVOC strategy consists of two steps: day-ahead optimal scheduling and intra-day optimal adjustment. In the first step, on-load tap changers (OLTCs) and capacitor banks (CBs) are scheduled to minimize the power losses based on the day-ahead forecasted loads and wind power outputs. The second step consists of two scenarios: normal operation and breakdown operation. Under normal operation, only the EVCs are scheduled for the within-day adjustment of reactive power compensation. The breakdown operation is implement when the bus voltage violation occurs, and the CBs are scheduled with the minimum switching numbers for fast voltage recovery. A time-adaptive delay method is applied to the breakdown operation to avoid overcompensation. An IEEE-30 bus system is used to verify the effectiveness of the VVOC strategy for power system integrated with wind farms.

A volt-var optimal control for power system integrated with wind farms considering the available reactive power from EV chargers

Model Predictive Control Approach for Building Microgrid Considering Dynamic Thermal Characteristics of Building

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Papers

Load curve smoothing strategy based on unified state model of different demand side resources

Load power smoothing control of distribution network including photovoltaic generation with energy storage from electric vehicles

A volt-var optimal control for power system integrated with wind farms considering the available reactive power from EV chargers

Model Predictive Control Approach for Building Microgrid Considering Dynamic Thermal Characteristics of Building