Optimal plug-in hybrid electric vehicles recharge in distribution power systems

Abstract

Plug-in hybrid electric vehicles are new alternatives that meet the efforts to develop more sustainable means of transportation and decreasing oil dependence. However, this trend could bring negative consequences to electric power systems, such as limits violations, power losses increasing, harmonics, and thermal limits violation on distribution transformers and conductors. To cope with some of those problems, this paper proposes a recharging process with the help of Artificial Immune Systems, so the voltage level in all buses is kept within the operational limits and no overload is observed. For this sake, besides distributing the load along the recharging period, capacitors installation to decrease electric losses and improve voltage levels during vehicles recharging is also considered. The results obtained render the proposed methodology as effective. Two IEEE sample systems are used to test the idea, so the results may be reproduced for research purposes.

Introduction

The popularization of electric propulsion in the transportation sector is a trend that meets the current proposals to reduce greenhouse gases emissions and represents a new alternative to oil dependency. Currently, several plug-in hybrid electric vehicles (PHEV) are being traded and are characterized by higher efficiency, fuel saving and low noise [1]. On the other hand, PHEVs still have greater prices compared to conventional models, due to their battery energy storage system [2].

As these vehicles increase their market share, another problem deserves attention from electricity companies. Their inclusion in power systems represents a large increase on load demand, causing many problems as voltage violation, power quality degradation, power losses increase, thermal limits violation on distribution transformers, reliability implications, harmonics and fault currents increase [3], [4], [5].

Several papers suggested solutions to cope with those problems, including controlling the recharging process to keep the voltage on acceptable levels, avoiding peak loads and transformers overload [6], [7]; using on-load tap transformers and capacitors to decrease losses [6].

On the other side, PHEV popularization could bring benefits to power systems, like load leveling; increasing generation capacity to the grid during high load periods without building new power plants; regulation and spinning reserve services and reduction of oil dependence and greenhouse gases emissions, yielding environmental improvements [8], [9].

Many researchers have been developing solutions for PHEV recharging. Clement-Nyns et al. proposed in [6] a coordinated charging to minimize power losses and maximize the main grid power factor. To perform optimization, the authors use quadratic and dynamic programming, since an exact forecast of household loads is not possible.

Coordinated recharging and linear programming are used to minimize PHEV recharging costs in [10]. It also investigates the consequences of inserting renewable generation into the grid. The interesting results obtained render the losses monitoring as a good strategy for reactive power, voltage level and branch loading control. The authors in [11] use Monte Carlo simulations in a coordinated recharging process to prove that maximizing power factor and also minimizing load variance are equivalent to power losses minimization.

In [12] a real-time smart load management control strategy is proposed and developed for the coordination of recharging process based on real-time minimization of total cost of generation plus the associated grid energy losses. In [13], a power losses minimization is performed by applying a time coordinated optimal power flow. They show that, through the control of PHEV storage units and on-load tap changers transformers, electric network operator can influence savings in energy losses.

Besides those approaches applied to losses minimization problem on [6], [7], [10], [11], [12], [13], evolutionary techniques are also used, as particle swarm optimization (PSO), which finds the optimal solution using a population of particles. However, this technique has some convergence problems, reaching non-optimal solutions. The mutation feature, present in Artificial Immune Systems (AIS), can avoid this problem [14].

Genetic Algorithms (GA) are also used as optimization tool in losses minimization problems. However, AIS searching process is quite different. While GA operators guide the population toward its fittest members, AIS searches for optimal solutions locally and in different regions of space shape at the same time. These features contributed for choosing AIS as the optimization tool in this paper.

This paper proposes a recharging policy on distribution power systems with the help of Artificial Immune Systems, so the voltage level in all buses are kept within limits and no overload is observed. For this sake, besides performing load leveling along the charging period, capacitors installation to decrease power losses and improve voltage levels is also considered.

This paper is organized as follows: In section II, PHEVs’ characteristics and their interaction with power systems are discussed. Section III discusses Artificial Immune Systems. The recharging process is investigated in section IV and the optimization solutions are presented. Section V displays the conclusions.