Seamless Integration of Renewable Generation and Plug-in Electric Vehicles into the Electrical Grid.

An imminent release of plug-in electric vehicles en masse will add substantial load to electrical power grids that are already operating near limits. Coordinated control of vehicle charging, however, can eliminate the need for expensive overhauls of grid infrastructure. Furthermore, the growing penetration of renewable energy sources provides an excellent opportunity to meet the increased electricity demand, but the challenge remains to tackle the variability and intermittency associated with renewable energy. Our research focuses on identifying and analyzing key issues regarding interactions between renewable generation, vehicle charging, and the power grid. In order to address these issues, we are designing control schemes that ensure seamless integration of newer forms of generation and load, while achieving satisfactory grid-level performance in areas such as loss minimization, voltage regulation, generation balancing and valley filling. Feedback control oriented analytical models have been developed to regulate aggregate demand by certain time deferrable loads (thermostatic loads, plug-in electric vehicle chargers). It is shown that, via a hysteresis-based pulse-width modulated type control, a linearized system response model can be established from the evolution of probability distribution of states (thermostat temperature, battery state-of-charge) of loads. It is shown that grid-level objectives, such as generation tracking and valley filling, can be satisfied by using only the aggregate power as measurement. A framework is presented to study the impact of synchronization in plug-in electric vehicle chargers on the voltage resiliency of electrical grid. It is shown that a fault-induced synchronized tripping of chargers can cause critical over-voltage situations in a distribution feeder. A non-linear state-space model is developed that can truly capture the complex, easily synchronizable, dynamics of hysteresis-based loads. It is reported that, under certain control input signals, such load aggregation can display instability in the form of period-adding cascade. A control method is proposed that optimally allocates photo-voltaic inverter output in a de-centralized way to minimize line losses and voltage deviations. While optimality of this de-centralized control law is proved under certain assumptions, its validity in a more practical scenario is also discussed and possible modifications are suggested.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99858/1/soumyak_1.pd

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

Fast-timescale Control Strategies for Demand Response in Power Systems.

Concerns over climate change have spurred an increase in the amount of wind and solar power generation on the grid. While these resources reduce carbon emissions, the physical phenomena that they rely on - wind and sunlight - are highly stochastic, making their generated power less controllable. Demand-side strategies, which modulate load in a controllable manner, have been proposed as a way to add flexibility to the grid. Resources with innate flexibility in their load profile are particularly suited to demand response (DR) applications. This work examines two such loads: heating, ventilation, and air conditioning (HVAC) systems, and plug-in electric vehicle (PEV) fleets. HVAC systems can vary the timing of power consumption due to the thermal inertia inherent in their associated building(s). The first part of this thesis explores the efficacy of using commercial HVAC for DR applications. Results are presented from an experimental testbed that quantify performance, in terms of accuracy in perturbing the load in a desired manner, as well as the efficiency of this process. PEVs offer very fast response times and may eventually represent a significant load on the power system. The second part of this thesis develops several control strategies to manage PEV power consumption in an environment where communication resources are limited, both to prevent detrimental system effects such as transformer overload, and to provide ancillary services such as frequency regulation to the grid.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116627/1/ianbeil_1.pd