Modelling dynamic demand response for plug-in hybrid electric vehicles based on real-time charging pricing

© The Institution of Engineering and Technology. Based on the benefits of real-time pricing both to individual users and the society as a whole, this study introduces a real-time charging price (RTCP) mechanism supported by an intelligent charging management module into plug-in hybrid electric vehicles (PHEVs) charging environment. The optimal RTCP is executed by a distributed algorithm using a utility model to maximise the whole charging system welfare. The willingness-to-charge parameter is derived to reflect the charging preferences of PHEV users and their different responses to the RTCP. Several scenarios are established to discuss the effect of both the RTCP and willingness-to-charge on charging load. The simulation results show that reasonable charging will be realised based on the optimal RTCP mechanism

Smart battery charger for electric mobility in smart grids

In this paper is presented the development of a smart batteries charger for Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs), aiming their integration in Smart Grids. The batteries charging process is controlled by an appropriate control algorithm, aiming to preserve the batteries lifespan. The main features of the equipment are the mitigation of the power quality degradation and the bidirectional operation, as Grid-to-Vehicle (G2V) and as Vehicle-to-Grid (V2G). During the charging process (G2V), the consumed current is sinusoidal and the power factor is unitary. Along the discharging process (V2G), when the equipment allows delivering back to the electrical power grid a small amount of the energy stored in the batteries, the current is also sinusoidal. The V2G mode of operation will be one of the main features of the Smart Grids, both to collaborate with the electrical power grid to increase stability, and to function as a distributed Energy Storage System (ESS). The functioning of the smart batteries charger is shown through simulation and experimental results, both during the charging (G2V) and the discharging (V2G) modes of operation. Also in this paper are shown and briefly described the roles of the key concepts related with the Smart Grids in terms of Systems and Functional Areas, Power Electronics Systems, and Electric Mobility.This work is financed by FEDER Funds, through the Operational Programme for Competitiveness Factors – COMPETE, and by National Funds through FCT – Foundation for Science and Technology of Portugal, under the project PTDC/EEA-EEL/104569/2008 and the project MIT-PT/EDAM-SMS/0030/2008

Artificial Intelligence Based Load Scheduling for Plugged in Electric Vehicles in Smart Grid

Plugged in Electric Vehicles (PHEV’s) are enormously eco friendly and highly appreciated transportation system in various developed countries. The PHEV’s integration into the conventional grid required significant modifications in order to control load shedding, reducing unit cost, even out peak demands in quest to make a grid reliable. Recent research studies are mainly focusing to counter these issues by employing multi objective optimization techniques. The objective of this method is to reduce demand; energy cost and enhances the presence of PHEV’s for charging and discharging by creating substantial scheduling vector. This research work has proposed split scheduling vector to charge and discharge an EV, to achieve the required results by minimizing peak to average demand ratio (PAR) and generate profit for the owners by decreasing the total energy cost

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

Comparison of intelligent charging algorithms for electric vehicles to reduce peak load and demand variability in a distribution grid

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium, price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage

Future strategic plan analysis for integrating distributed renewable generation to smart grid through wireless sensor network: Malaysia prospect

AbstractIntegration of Distributed Renewable Generation (DRG) to the future Smart Grid (SG) is one of the important considerations that is highly prioritized in the SG development roadmap by most of the countries including Malaysia. The plausible way of this integration is the enhancement of information and bidirectional communication infrastructure for energy monitoring and controlling facilities. However, urgency of data delivery through maintaining critical time condition is not crucial in these facilities. In this paper, we have surveyed state-of-the-art protocols for different Wireless Sensor Networks (WSNs) with the aim of realizing communication infrastructure for DRG in Malaysia. Based on the analytical results from surveys, data communication for DRG should be efficient, flexible, reliable, cost effective, and secured. To meet this achievement, IEEE802.15.4 supported ZigBee PRO protocol together with sensors and embedded system is shown as Wireless Sensor (WS) for DRG bidirectional network with prospect of attaining data monitoring facilities. The prospect towards utilizing ZigBee PRO protocol can be a cost effective option for full integration of intelligent DRG and small scale Building-Integrated Photovoltaic (BIPV)/Feed-in-Tariff (FiT) under SG roadmap (Phase4: 2016–2017) conducted by Malaysia national utility company, Tenaga Nasional Berhad (TNB). Moreover, we have provided a direction to utilize the effectiveness of ZigBee-WS network with the existing optical communication backbone for data importing from the end DRG site to the TNB control center. A comparative study is carried out among developing countries on recent trends of SG progress which reveals that some common projects like smart metering and DRG integration are on priority