Mohammad Nikkhah Mojdehi

Modeling and revenue estimation of EV as reactive power service provider

Moving toward smart grid makes the distribution systems more active. In this dynamic environment, introducing new components such as Electric Vehicle (EV) can provide opportunities for Distribution System Operator (DSO) to improve the efficiency, economics, and sustainability of the production and distribution of electricity. For example, since reactive power support from EVs has short response time and does not affect the battery, reactive power support is a promising ancillary service that can be provided by EVs. This ancillary service is gaining more importance at distribution level where due to increased number of loads and the network topology, tracking the frequent changes in loads requires real time actions from local providers close to the loads. In this paper, we present a new model of EV operating as a reactive power service provider. We have included power ripple in the charger as a constraint in the proposed model. Our simulation results show the revue potential of providing reactive power service by EVs. This revenue amount is higher during peak hours because of increased demand from the DSO.

A methodology to design a stochastic cost efficient DER scheduling considering environmental impact

Electric power generation and transportation sectors are considered as main sources of gas emission today. Renewable energy and Electric Vehicles (EV) show potential as promising solutions for emission reduction and energy cost saving. However, the integration of renewable energy generation into the electric grid can be difficult, because of the source intermittency and inconsistency with energy usage; uncontrolled EV charging can also impose more burdens on power systems. Those situations can be improved through coordinated charging of EVs and optimized operation of distributed generators (DG) that not only mitigates fluctuations in generation and supply, but also reduces energy cost and the emission of pollutants (CO2, SO2, and NOx). Emerging smart grid also brings new options for Distribution System Operator (DSO) toward efficient and sustainable operation of the network. One of these options is the use of Distributed Energy Resources (DER) including DG, EV, and Demand Response (DR). Operating DER has several advantages for DSO such as having DER close to load centers which reduces total network power loss. Since DSO has several energy sources to satisfy the electric load demand in the network, it is necessary to deploy optimal scheduling for efficient usage of available energy resources. In this paper we discuss a stochastic scheduling in the distribution network considering uncertainty in renewable energy generation. The proposed model can be used to analyse the effect of using DGs and EVs on emission and operation costs of the network. Results clearly shows that cost saving could be achieved with proper planning and coordination of various DERs.

An On-Demand Compensation Function for an EV as a Reactive Power Service Provider

Rapid growth in the deployment of electric vehicles (EVs) is creating opportunities for system operators to improve the reliability and sustainability of electricity delivery system, while reducing the operating cost. EVs can respond quickly, improve system stability, and provide reactive power support without battery wear. Therefore, EVs could be a promising source of reactive power when they are connected to smart charging equipment. However, under certain scenarios, reactive power support may raise the vehicle charging cost by shifting part of charging power to times of the day when the price of electricity is higher. Participation of EVs in an ancillary service market for reactive power will thus require some level of compensation for EV owners. In this paper, we present a framework for the calculation of reactive power supply function for EVs. We define an objective function representing charging/discharging cost of EVs and then minimize the cost under realistic constraints. An algorithm is then introduced that extracts the EVs supply function for providing on-demand reactive power service at minimum cost. Thus, the system operator can include EVs, as reactive power service providers (RPSPs) along with other service providers, to meet the on-demand need of the reactive power. Simulation results indicate the EVs ability to provide reactive power service during on-peak periods, when the system operators need for reactive power is most likely high, at almost no cost to the EV owner.

Estimation of the Battery Degradation Effects on the EV Operating Cost during Charging/Discharging and Providing Reactive Power Service

Dynamic environment of the power system can be better controlled by the smart usage of electric vehicles (EVs). EVs with their diverse capabilities can create opportunities for Distribution System Operator (DSO) to improve the efficiency, economics, and sustainability of power delivery system. For instance, reactive power support can be provided by EVs quickly, when needed by the DSO. This type of ancillary service is becoming a necessity, due to higher power demands and continuous change in supply-demand environment. On the other hand, high battery price discourages consumers to purchase EVs. Therefor, creating ways to reduce the overall battery cost by generating revenue through participation in the power market, could be a win-win situation for both, EV owner and the DSO. Revenue generation for EVs could be achieved by supplying active and/or reactive power. In this paper, we present a model of EV operating as a reactive power service provider, considering the battery degradation, as a function of active power flow. The developed model includes charger technical constraints. Simulation results show optimal operating cost estimation, taking into consideration the effect of the battery degradation on charging, discharging and reactive power service of the EV under different scenarios. Results indicate significant change in active power charging and discharging patterns when the battery degradation cost is included. Revenue generating potential of providing reactive power service by EVs could be an encouraging fact for EVs to participate in reactive power market.

Market equilibrium of distribution network with alternative energy resources

Electricity distribution networks are rapidly becoming more complex. Distributed generation (DG) is increasing and some DG units are intermittent renewables such as solar or wind. Moreover, plug-in electric vehicles (EVs) are expected to be deployed in large numbers over the next decade. These changes present opportunities as well as challenges for reliable and efficient operation of distribution networks. In this paper, we present a new stochastic model in which market clearing prices are endogenously determined. Potential suppliers include the main grid supply, a range of different DG technologies within the distribution network, and EVs operated in vehicle-to-grid (V2G) mode. We allow for supply uncertainties for renewable resources and also allow for uncertainties in EV availability for charging and discharging. Using stochastic optimal power flow (SOPF) based on monte-carlo simulation, we analyze the effects of operating distributed energy resources (DERs) on social welfare considering emission taxes.

Distributed generations scheduling in micro-grid considering CO 2 emission cost

Developments in distributed generation (DG) technologies, information and communication technologies, environmental concerns, liberalization in electricity markets and restructuring encourage operation of DGs in smart grid. High penetration of DG resources is increasing worldwide. In this paper we present an analyze of the effect of CO2 emission cost on distribution network scheduling with photovoltaic (PV) and wind turbine as power sources. The proposed model in this paper considers retail price of distribution network and price of generated electricity by PV and wind turbine. Numerical simulations are carried out used a 33-bus test distribution network. Test results show that the current policy to determine CO2 emission tax, considering the price of generated electricity by DGs, is not always supportive of operation of DGs at their maximum output.

Transportation electrification: From vehicle to grid integration

Rising fuel prices, depleting fossil fuels, and the long-term benefits of clean energy have all provided the opportunity to comprehensively address the transportation electrification and integration of transportation with electric utilities. Electric vehicles (EVs) have many benefits as compared to conventional gasoline cars. Moreover, electrification of transportation systems would enable increased electricity generation from carbon-free and renewable energy sources, such as wind, solar, and hydro. It is anticipated that the electric utility and transportation systems in the United States will become increasingly integrated and indistinguishable from each other due to the electrification of the transportation system. This panel will consist of researchers coming from academy and industry. The presentations by the panel will give a broad coverage from electric vehicles to integration and impact of electric vehicles to the grid. From vehicle perspective, the panel will focus on typical EV configurations, challenges associated with EV energy management and high performance traction control technology using artificial neural networks. Regarding EV grid integration, the panel will discuss charging management of EVs, EV integration with renewables, and techniques of using a fleet of EVs in support of automatic generation control in a smart grid framework. The panel presentation and discussion should build a foundation for one of the most critical technological areas to enhance U.S. energy security and environmental sustainability.

Microgrid interoperability: First steps from policy to implementation

There have been no shortage of discussions, policies, executive orders, special committees, conferences and natural disasters to enumerate the benefits of microgrids. However, as we pass the 10 year anniversary of Hurricane Katrina and the 2 year anniversary of Superstorm Sandy the proliferation of microgrids is still seemingly trapped in a wave of dialogue and a limited number of projects which resemble the Department of Energys definition of a localized resiliency solution - WHY? Ultimately, the widespread implementation of microgrids will be driven by a clear and logical approach to addressing baseline attributes of these systems; self-healing, dynamic participation and asset optimization are but a few. This paper will examine an approach for one of the first essential attributes to be confronted in the planning and design of microgrids, which is to understand the parameters for seamless transition between grid-tied and island modes of operation.

Energy and cost minimization of bidirectional frequency regulation service by EV following FERC order 755

Increasing share of renewable energy sources in the electric sector, forces the system operators to include new resources for frequency regulations with fast ramping. Electric vehicles (EVs) with fast charging and short battery reaction time are becoming promising source for frequency regulations. Therefore, it is worthwhile to evaluate EVs abilities and associated cost to participate in the frequency regulation activity. In this paper, we first present a linear model of EV operating in charging/discharging mode and impact of battery degradation during these activities. We then define a cost function for EV operation and its minimization using linear programming. After calculating the optimal operating points of EV, a novel framework was developed to calculate optimal bidding components of EV, regulation capacity and energy cost function to participate in the regulation market. Simulation results show the efficiency of the developed linear model. Results also provide pathways for possible opportunities of revenue stream for the EV owner, by offering the regulation up/down services, without limiting the EV owners level of comfort.

Minimization of energy usage and cost for EV during reactive power service

Electric Vehicle (EV) becoming a promising reactive power service provider because of its short response time with no battery degradation during this service. Also EV would allow efficient adjustment of power flows in response to frequent changes in loads. In this paper we present a novel structure to evaluate the reactive power service potential of EVs. We formulate a linear program to minimize the operating cost of an EV that includes the battery degradation cost, under a range of practical constraints. These constraints include owners desired state of charges and limitation in the current ripple from the DC-link capacitor of the EV charger. The developed optimization framework yields EVs optimal charging/discharging and reactive power service (injection/absorption) schedules. We also introduce an algorithm capable of determining the estimated compensation for the EV owner under different market structure and when real time events force the DSO to ask for more reactive power than pre-scheduled amount.