Khizir Mahmud

Improved peak shaving in grid-connected domestic power systems combining photovoltaic generation, battery storage, and V2G-capable electric vehicle

Strategic use of domestic battery storage in households with a V2G-capable electric vehicle and photovoltaic generation is shown to be capable of shaving the peak loading on the electricity distribution grid under realistic operating conditions by up to 37%. The additional degree of freedom provided by combining the EV and domestic storage is shown to enable additional reductions in peak grid load. A smart control algorithm is described for coordinating the system components to reduce peak grid load and improve power quality.

A review of computer tools for analyzing the impact of electric vehicles on power distribution

This paper reviews the various computer tools that have been reported for modeling the impacts of electrical vehicles on the power distribution grid. Forty four computer tools have been identified and summarised to facilitate selection of the most appropriate tools for specific tasks. Typical applications of the tools include vehicle design, analysis, control, grid integration and impact, market scheduling, and energy management. No single tool addresses all requirements, however sufficient information is provided to enable researchers to choose the appropriate combination of tools to meet specific research objectives.

Domestic peak-load management including vehicle-to-grid and battery storage unit using an artificial neural network

Controlled charging and discharge of electric vehicles (EVs) in distributed power systems can reduce the peak demand on the grid. This paper presents an energy management strategy (EMS) using an artificial neural network to shave the domestic peak grid load by the coordinated response of distributed energy resource (DER) units including photovoltaic (PV) systems, V2G (vehicle to grid)-capable EVs, and battery energy storage systems (BESS). The developed EMS is implemented on a test system including 15 houses and the realistic load pattern of California, U.S. From the simulation results for this network it is found that an artificial-neural-network controller can effectively coordinate the system to reshape the load curve and shave the domestic peak loading by up to 77%.

Mitigating the impact of rapid changes in photovoltaic power generation on network voltage

Intermittent shading by trees and clouds can cause rapid changes in photovoltaic power generation which may introduce voltage variations in low-voltage distribution networks. Investigations into the impact of these rapid changes in generation on network voltage sag/swell show they may be mitigated using battery energy storage systems. A test system consisting of nine houses with real PV irradiance data, battery, and load were used in the modelling. From the simulation results it was found that battery storage can reduce the associated voltage variations, depending on its location. A charging-discharging algorithm for the battery was developed and it was found that if the battery is placed and controlled appropriately the voltage variations and peak load on the main grid may be reduced significantly.

Towards an internet of energy

The current model of centralized electricity generation, transmission and distribution is under pressure to change for a variety of reasons; environmental concerns are driving a shift away from large coal-fired generation systems to increasing adoption of renewable energy sources, which tend to be distributed and not always available on demand, and hence requiring distributed storage support. Moreover, to support electric vehicles, energy needs to be provided as a service to consumers independent of location, rather than a product delivered and billed to a fixed location. In this work, we compare and contrast modern internet and energy networks and services, identifying key functionalities and the main technical challenges to be faced in transforming the electricity distribution system to a flexible yet reliable and robust platform for the exchange of electrical energy.

5.6 Energy Management Softwares and Tools

Software tools are reviewed for assisting in the analysis, design, and management of electrical energy systems incorporating renewable energy sources and/or communications for monitoring and control. Over 200 tools are classified by zone, domain, and layer within the CEN-CENELEC-ETSI Smart Grid Reference Architecture. The purpose, availability, source, and application of each tool are briefly described, and a summary of the strengths of selected tools is provided.