Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-in Hybrid Electric Buses

We discuss a recently introduced ECO-driving concept known as SPONGE in the context of Plug-in Hybrid Electric Buses (PHEB)'s.Examples are given to illustrate the benefits of this approach to ECO-driving. Finally, distributed algorithms to realise SPONGE are discussed, paying attention to the privacy implications of the underlying optimisation problems.Comment: This paper is recently submitted to the IEEE Transactions on Automation Science and Engineerin

Distributed charging management of multi‐class electric vehicles with different charging priorities

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166242/1/gtd2bf02710.pd

Topics in Electromobility and Related Applications

In this thesis, we mainly discuss four topics on Electric Vehicles (EVs) in the context of smart grid and smart transportation systems. The first topic focuses on investigating the impacts of different EV charging strategies on the grid. In Chapter 3, we present a mathematical framework for formulating different EV charging problems and investigate a range of typical EV charging strategies with respect to different actors in the power system. Using this framework, we compare the performances of all charging strategies on a common power system simulation testbed, highlighting in each case positive and negative characteristics. The second topic is concerned with the applications of EVs with Vehicle-to-Grid (V2G) capabilities. In Chapter 4, we apply certain ideas from cooperative control techniques to two V2G applications in different scenarios. In the first scenario, we harness the power of V2G technologies to reduce current imbalance in a three-phase power network. In the second scenario, we design a fair V2G programme to optimally determine the power dispatch from EVs in a microgrid scenario. The effectiveness of the proposed algorithms are verified through a variety of simulation studies. The third topic discusses an optimal distributed energy management strategy for power generation in a microgrid scenario. In Chapter 5, we adapt the synchronised version of the Additive-Increase-Multiplicative-Decrease (AIMD) algorithms to minimise a cost utility function related to the power generation costs of distributed resources. We investigate the AIMD based strategy through simulation studies and we illustrate that the performance of the proposed method is very close to the full communication centralised case. Finally, we show that this idea can be easily extended to another application including thermal balancing requirements. The last topic focuses on a new design of the Speed Advisory System (SAS) for optimising both conventional and electric vehicles networks. In Chapter 6, we demonstrate that, by using simple ideas, one can design an effective SAS for electric vehicles to minimise group energy consumption in a distributed and privacy-aware manner; Matlab simulation are give to illustrate the effectiveness of this approach. Further, we extend this idea to conventional vehicles in Chapter 7 and we show that by using some of the ideas introduced in Chapter 6, group emissions of conventional vehicles can also be minimised under the same SAS framework. SUMO simulation and Hardware-In-the-Loop (HIL) tests involving real vehicles are given to illustrate user acceptability and ease of deployment. Finally, note that many applications in this thesis are based on the theories of a class of nonlinear iterative feedback systems. For completeness, we present a rigorous proof on global convergence of consensus of such systems in Chapter 2

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

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

Optimal Configuration of Extreme Fast Charging Stations Integrated with Energy Storage System and Photovoltaic Panels in Distribution Networks

Extreme fast charging (XFC) for electric vehicles (EVs) has emerged recently because of the short charging period. However, the extreme high charging power of EVs at XFC stations may severely impact distribution networks. This paper addresses the estimation of the charging power demand of XFC stations and the design of multiple XFC stations with renewable energy resources in current distribution networks. First, a Monte Carlo (MC) simulation tool was created utilizing the EV arrival time and state-of-charge (SOC) distributions obtained from the dataset of vehicle travel surveys. Various impact factors are considered to obtain a realistic estimation of the charging power demand of XFC stations. Then, a method for determining the optimal energy capacity of the energy storage system (ESS), ESS rated power, and size of photovoltaic (PV) panels for multiple XFC stations in a distribution network is presented, with the goal of achieving an optimal configuration. The optimal power flow technique is applied to this optimization so that the optimal solutions meet not only the charging demand but also the operational constraints related to XFC, ESS, PV panels, and distribution networks. Simulation results of a use case indicate that the presented MC simulation can estimate approximate real-world XFC charging demand, and the optimized ESS and PV units in multiple XFC stations in the distribution network can reduce the annual total cost of XFC stations and improve the performance of the distribution network

HVAC-based hierarchical energy management system for microgrids

With the high penetration of renewable energy into the grid, power fluctuations and supply-demand power mismatch are becoming more prominent, which pose a great challenge for the power system to eliminate negative effects through demand side management (DSM). The flexible load, such as heating, ventilation, air conditioning (HVAC) system, has a great potential to provide demand response services in the electricity grids. In this thesis, a comprehensive framework based on a forecasting-management optimization approach is proposed to coordinate multiple HVAC systems to deal with uncertainties from renewable energy resources and maximize the energy efficiency. In the forecasting stage, a hybrid model based on Multiple Aggregation Prediction Algorithm with exogenous variables (MAPAx)-Principal Components Analysis (PCA) is proposed to predict changes of local solar radiance, vy using the local observation dataset and real-time meteorological indexes acquired from the weather forecast spot. The forecast result is then compared with the statistical benchmark models and assessed by performance evaluation indexes. In the management stage, a novel distributed algorithm is developed to coordinate power consumption of HVAC systems by varying the compressors’ frequency to maintain the supply-demand balance. It demonstrates that the cost and capacity of energy storage systems can be curtailed, since HVACs can absorb excessive power generation. More importantly, the method addresses a consensus problem under a switching communication topology by using Lyapunov argument, which relaxes the communication requirement. In the optimization stage, a price-comfort optimization model regarding HVAC’s end users is formulated and a proportional-integral-derivative (PID)-based distributed algorithm is thus developed to minimize the customer’s total cost, whilst alleviating the global power imbalance. The end users are motivated to participate in energy trade through DSM scheme. Furthermore, the coordination scheme can be extended to accommodate battery energy storage systems (BESSs) and a hybrid BESS-HVAC system with increasing storage capacity is proved as a promising solution to enhance its selfregulation ability in a microgrid. Extensive case studies have been undertaken with the respective control strategies to investigate effectiveness of the algorithms under various scenarios. The techniques developed in this thesis has helped the partnership company of this project to develop their smart immersion heaters for the customers with minimum energy cost and maximum photovoltaic efficiency

Frequency Regulation with Heterogeneous Energy Resources: A Realization using Distributed Control

This paper presents one of the first real-life demonstrations of coordinated and distributed resource control for secondary frequency response in a power distribution grid. We conduct a series of tests with up to 69 heterogeneous active devices consisting of air handling units, unidirectional and bidirectional electric vehicle charging stations, a battery energy storage system, and 107 passive devices consisting of building loads and photovoltaic generators. Actuation commands for the test devices are obtained by solving an economic dispatch problem at every regulation instant using distributed ratio-consensus, primal-dual, and Newton-like algorithms. The distributed control setup consists of a set of Raspberry Pi end-points exchanging messages via an ethernet switch. The problem formulation minimizes the sum of device costs while tracking the setpoints provided by the system operator. We demonstrate accurate and fast real-time distributed computation of the optimization solution and effective tracking of the regulation signal by measuring physical device outputs over 40-minute time horizons. We also perform an economic benefit analysis which confirms eligibility to participate in an ancillary services market and demonstrates up to $53K of potential annual revenue for the selected population of devices