Distributed multi-agent algorithm for residential energy management in smart grids

Distributed renewable power generators, such as solar cells and wind turbines are difficult to predict, making the demand-supply problem more complex than in the traditional energy production scenario. They also introduce bidirectional energy flows in the low-voltage power grid, possibly causing voltage violations and grid instabilities. In this article we describe a distributed algorithm for residential energy management in smart power grids. This algorithm consists of a market-oriented multi-agent system using virtual energy prices, levels of renewable energy in the real-time production mix, and historical price information, to achieve a shifting of loads to periods with a high production of renewable energy. Evaluations in our smart grid simulator for three scenarios show that the designed algorithm is capable of improving the self consumption of renewable energy in a residential area and reducing the average and peak loads for externally supplied power

Life Cycle Analysis and Optimization of Wireless Charging Technology to Enhance Sustainability of Electric and Autonomous Vehicle Fleets

The transportation sector is undergoing a major transformation. Emerging technologies play indispensable roles in driving this mobility shift, including vehicle electrification, connection, and automation. Among them, wireless power transfer (WPT) technology, or commonly known as wireless charging technology, is in the spotlight in recent years for its applicability in charging electric vehicles (EVs). On one hand, WPT for EVs can solve some of the key challenges in EV development, by: (1) reducing range anxiety of EV owners by allowing “charging while driving”; and (2) downsizing the EV battery while still fulfilling the same trip distance. More en-route wireless charging opportunities result in battery downsizing, which reduces the high EV price and vehicle weight and improves fuel economy. On the other hand, WPT infrastructure deployment is expensive and resource-intensive, and results in significant economic, environmental, and energy burdens, which can offset these benefits. This research aims to develop and apply a life cycle analysis and optimization framework to examine the role of wireless charging technology in driving sustainable mobility. This research highlights the technology trade-offs and bridges the gap between technology development and deployment by establishing an integrated life cycle assessment and life cycle cost (LCA-LCC) model framework to characterize and evaluate the economic, environmental, and energy performance of WPT EV systems vs. conventional plug-in charging EV systems. Life cycle optimization (LCO) techniques are used to improve the life cycle performance of WPT EV fleets. Based on case studies, this research draws observations and conditions under which wireless charging technology has potential to improve life cycle environmental, energy, and economic performance of electric vehicle fleets. This study begins with developing LCA-LCC and LCO models to evaluate stationary wireless power transfer (SWPT) for transit bus systems. Based on a case study of Ann Arbor bus systems, the wirelessly charged battery can be downsized to 27–44% of a plug-in charged battery, resulting in vehicle lightweighting and fuel economy improvement in the use phase that cancels out the burdens of large-scale infrastructure. Optimal siting strategies of WPT bus charging stations reduced life cycle costs, greenhouse gases (GHG), and energy by up to 13%, 8%, and 8%, respectively, compared to extreme cases of “no charger at any bus stop” and “chargers at every stop”. Next, the LCA-LCC and LCO model framework is applied to evaluate the economic, energy, and environmental feasibility of dynamic wireless power transfer (DWPT) for charging passenger cars on highways and urban roadways. A case study of Washtenaw County indicates that optimal deployment of DWPT electrifying up to about 3% of total roadway lane-miles reduces life cycle GHG emissions and energy by up to 9.0% and 6.8%, respectively, and enables downsizing of the EV battery capacity by up to 48% compared to the non-DWPT scenarios and boosts EV market penetration to around 50% of all vehicles in 20 years. Finally, synergies of WPT and autonomous driving technologies in enhancing sustainable mobility are demonstrated using the LCA framework. Compared to a plug-in charging battery electric vehicle system, a wireless charging and shared automated battery electric vehicle (W+SABEV) system will pay back GHG emission burdens of additional infrastructure deployment within 5 years if the wireless charging utility factor is above 19%.PHDNatural Resources & EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147602/1/bizc_1.pd

Architectures for smart end-user services in the power grid

Abstract-The increase of distributed renewable electricity generators, such as solar cells and wind turbines, requires a new energy management system. These distributed generators introduce bidirectional energy flows in the low-voltage power grid, requiring novel coordination mechanisms to balance local supply and demand. Closed solutions exist for energy management on the level of individual homes. However, no service architectures have been defined that allow the growing number of end-users to interact with the other power consumers and generators and to get involved in more rational energy consumption patterns using intuitive applications. We therefore present a common service architecture that allows houses with renewable energy generation and smart energy devices to plug into a distributed energy management system, integrated with the public power grid. Next to the technical details, we focus on the usability aspects of the end-user applications in order to contribute to high service adoption and optimal user involvement. The presented architecture facilitates end-users to reduce net energy consumption, enables power grid providers to better balance supply and demand, and allows new actors to join with new services. We present a novel simulator that allows to evaluate both the power grid and data communication aspects, and illustrate a 22% reduction of the peak load by deploying a central coordinator inside the home gateway of an end-user

Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies

[EN] The market for electric vehicles (EVs) has grown with each year, and EVs are considered to be a proper solution for the mitigation of urban pollution. So far, not much attention has been devoted to the use of EVs for public transportation, such as taxis and buses. However, a massive introduction of electric taxis (ETs) and electric buses (EBs) could generate issues in the grid. The challenges are different from those of private EVs, as their required load is much higher and the related time constraints must be considered with much more attention. These issues have begun to be studied within the last few years. This paper presents a review of the different approaches that have been proposed by various authors, to mitigate the impact of EBs and ETs on the future smart grid. Furthermore, some projects with regard to the integration of ETs and EBs around the world are presented. 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