Omar Hafez

Optimal PHEV charging in coordination with distributed generation operation in distribution systems

Increase in energy demand is one of the major challenges that utilities are faced with, which results in increase in environmental pollution and global warming. The transport sector has a significant share in the energy demand as well as environmental pollution. In Canada, almost 35% of the total energy demand is from the transport sector and it is the second largest source of greenhouse gas (GHG) emissions. The government of Ontario, Canada, has aimed to move toward a green energy economy, aimed towards increased penetration of renewable energy sources and Plug-in Hybrid Electric Vehicle (PHEV) technology. In this paper, an optimal power flow (OPF) based optimization framework considering two different objectives, minimizing feeder losses and PHEV charging cost, are presented to understand the impact of PHEV charging on distribution networks. Three different charging periods are considered and the impact of the Ontario Time-of-Use (TOU) tariff on PHEV charging schedules is examined. The impact of PHEV charging on distribution systems in the presence of renewable energy sources is also discussed.

Queuing Analysis Based PEV Load Modeling Considering Battery Charging Behavior and Their Impact on Distribution System Operation

This paper presents a queuing analysis-based method for modeling the 24-h charging load profile of a plug-in electric vehicle (PEV) charging station. The queuing model considers the arrival of PEVs as a non-homogeneous Poisson process with different arrival rates over the day. The first PEV charging load profile assumes customer convenience as the factor that influences the hourly arrival rate of vehicles at the station, while the second profile is developed assuming that customers would respond to PEV charging prices and arrival rates are accordingly affected. One of the main contributions of this paper is to model the PEV service time considering different factors such as the state-of-charge of the vehicle battery, as well as the effect of the battery charging behavior. The impact of PEV load models on distribution systems is studied for a deterministic case, and the impact of uncertainties is examined and compared using the stochastic optimal power flow and the model predictive control approaches.

Optimal break-even distance for design of microgrids

Around the world there are many rural areas need access to electricity, extend the transmission line is one option. However, the long distance between the nearest main grid and the rural system as well as the costs of transmission line expansion rapidly increasing makes grid extension difficult, costly and economically unviable. Therefore, using microgrid technology with renewable energy options to meet electricity demand in remote locations becomes more attractive. In this paper the break-even distance which makes electricity from microgrid cost effective over the one form main grid is calculated. Moreover, the Net Present Costs (NPC) of both providing electricity through the microgrid and the main grid are calculated and compared. Five different cases including a diesel-only, a fully renewable-based, a diesel-renewable mixed, a solar-only, and a wind-only microgrid configurations are designed, to compare and evaluate their economics with the main grid. The well known energy modeling software for hybrid renewable energy systems, HOMER is used in the studies reported in this paper.

Integrating EV Charging Stations as Smart Loads for Demand Response Provisions in Distribution Systems

This paper presents a mathematical model for representing the total charging load at an electric vehicle charging station (EVCS) in terms of controllable parameters; the load model developed using a queuing model followed by a neural network (NN). The queuing model constructs a data set of plug-in electric vehicle (PEV) charging parameters which are input to the NN to determine the controllable EVCS load model. The queuing model considers arrival of PEVs as a non-homogeneous Poisson process, while the service time is modeled considering detailed characteristics of battery. The smart EVCS load is a function of number of PEVs charging simultaneously, total charging current, arrival rate, and time; and various class of PEVs. The EVCS load is integrated within a distribution operations framework to determine the optimal operation and smart charging schedules of the EVCS. Objective functions from the perspective of the local distribution company and EVCS owner are considered for studies. A 69-bus distribution system with an EVCS at a specific bus, and smart load model is considered for the studies. The performance of a smart EVCS vis-à-vis an uncontrolled EVCS is examined to emphasize the demand response contributions of a smart EVCS and its integration into distribution operations.

Queuing analysis based siting of PEV charging stations considering on distribution system impact

This paper presents a new approach using queuing analysis to determine the best location of plug-in electric vehicle (PEV) charging stations considering the resulting charging load and their impact on distribution system operations. A large database of mobility statistics available from Waterloo Region Transportation Tomorrow Survey (TTS) is used to model the arrival rate of PEVs at the charging station as continuous and random, non-homogeneous Poisson processes. Using the developed arrival rate profiles, appropriate queuing models are developed to estimate the 24-hour charging load profile at a PEV charging station. A distribution operations model is used to identify the optimal siting of charging stations while reducing the distribution losses and bus voltage deviations on distribution feeders.

The impact of smart PEV loads in the smart grid considering demand response provisions

This paper presents a comprehensive study of the impact of smart charging load at an electric vehicle charging station (EVCS) in distribution system considering demand response. Objective functions from the perspective of the load dispatch center (LDC) and EVCS owner are considered for studies. A 69-bus distribution system with an EVCS at a specific bus, and smart load is considered for the studies. The performance of a smart EVCS with peak demand signal vis-à-vis without peak demand signal is examined to emphasize the demand response (DR) contributions of a smart EVCS and its integration into smart grid operations.

Modeling of PEV charging load using queuing analysis and its impact on distribution system operation

This paper presents a novel approach for modeling the 24-hour charging demand profile of a plug-in electric vehicle (PEV) charging station using queuing analysis. The proposed queuing model considers the arrival of PEVs as a non-homogeneous Poisson process with different arrival rates over the day. A distribution optimal power flow (OPF) model is used to study the impact of the PEV charging load of the charging station on distribution system operation. Various objective functions, such as total feeder losses, energy drawn by the local distribution company (LDC) and total cost of energy drawn by LDC are considered in this paper.