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Parameter Identification of Aggregated Thermostatically Controlled Loads for Smart Grids Using PDE Techniques

Scott Moura
Bendtsen, Jan
Ruiz, Victor
2014

This paper develops methods for model identification of aggregated thermostatically controlled loads (TCLs) in smart grids, via partial differential equation (PDE) techniques. Control of aggregated TCLs provides a promising opportunity to mitigate the mismatch between power generation and demand, thus enhancing grid reliability and enabling renewable energy penetration. To this end, this paper focuses on developing parameter identification algorithms for a PDE-based model of aggregated TCLs. First, a two-state boundary-coupled hyperbolic PDE model for homogenous TCL populations is derived...

Better Batteries Through Electrochemistry

Scott Moura
Perez, Hector E.
2014

This article introduces key concepts in Electrochemical-based Control (ECC) systems for batteries, and highlights the fundamentals of battery electrochemistry, state-of-charge/state-of-health (SOC/SOH) estimation, and constrained control. Research on battery SOC/SOH estimation has experienced considerable growth, and can be categorized under equivalent circuit models (ECM) or EChem model-based algorithms. EChem models capture the spatiotemporal dynamics of lithium-ion concentration, electric potential, and intercalation kinetics. The most fundamental reduced EChem model is the single-...

Model Predictive Control of Residential Baseboard Heaters with Distributed System Architecture

Burger, Eric M.
Perez, Hector E.
Scott Moura
2014

Typical residential HVAC systems employ mechanical or hard-coded deadband control behaviors that are unresponsive to changing energy costs and weather conditions. In this paper, we investigate the potential of electric baseboard heaters to maintain a comfortable temperature while optimizing electricity consumption given weather forecasts and price data. We first propose a distributed system architecture that utilizes mobile application platforms. We then develop, assemble, and deploy a sensor network and Internet server to collect real-time temperature data from an apartment. With these...

Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles

Sun, Chao
Hu, Xiaosong
Scott Moura
Sun, Fengchun
2015

The performance and practicality of predictive energy management in hybrid electric vehicles (HEVs) are highly dependent on the forecast of future vehicular velocities, both in terms of accuracy and computational efficiency. In this brief, we provide a comprehensive comparative analysis of three velocity prediction strategies, applied within a model predictive control framework. The prediction process is performed over each receding horizon, and the predicted velocities are utilized for fuel economy optimization of a power-split HEV. We assume that no telemetry or on-board sensor...

Fast Charging Batteries via Electrochemical Model-based Control

Scott Moura
2014

Title: Fast Charging Batteries via ElectroChemical Model-Based Control In telecommunications, there were 5.2B active mobile handsets and over 1.7B mobile phone sales worldwide for 2012. Mobile phones are also a powerful tool for solving poverty and financial inequity in third world countries. In electrified transportation, there were 53,000 were plug-in electric vehicles sold in the U.S. for 2012. Despite growing sales, range anxiety is considered the largest inhibitor of electrified transportation. Significant reduction in charge times, e.g. comparable to filling a gas tank, would...

Quantifying EV Battery End-of-Life Through Analysis of Travel Needs with Vehicle Powertrain Models

Saxena, Samveg
Le Floch, Caroline
MacDonald, Jason
Scott Moura
2015

Electric vehicles enable clean and efficient transportation, however concerns about range anxiety and battery degradation hinder EV adoption. The common definition for battery end-of-life is when 70–80% of original energy capacity remains, however little analysis is available to support this retirement threshold. By applying detailed physics-based models of EVs with data on how drivers use their cars, we show that EV batteries continue to meet daily travel needs of drivers well beyond capacity fade of 80% remaining energy storage capacity. Further, we show that EV batteries with...

Comparison of Velocity Forecasting Strategies for Predictive Control in HEVs

Sun, Chao
Hu, Xiaosong
Scott Moura
Sun, Fengchun
2014

The performance of model predictive control (MPC) for energy management in hybrid electric vehicles (HEVS) is strongly dependent on the projected future driving profile. This paper proposes a novel velocity forecasting method based on artificial neural networks (ANN). The objective is to improve the fuel economy of a power-split HEV in a nonlinear MPC framework. In this study, no telemetry or on-board sensor information is required. A comparative study is conducted between the ANN-based method and two other velocity predictors: generalized exponentially varying and Markov-chain models. The...

Dynamic Traffic Feedback Data Enabled Energy Management in Plug-in Hybrid Electric Vehicles

Sun, Chao
Scott Moura
Hu, Xiaosong
Hedrick, J. Karl
Sun, Fengchun
2015

Recent advances in traffic monitoring systems have made real-time traffic velocity data ubiquitously accessible for drivers. This paper develops a traffic data-enabled predictive energy management framework for a power-split plug-in hybrid electric vehicle (PHEV). Compared with conventional model predictive control (MPC), an additional supervisory state of charge (SoC) planning level is constructed based on real-time traffic data. A power balance-based PHEV model is developed for this upper level to rapidly generate battery SoC trajectories that are utilized as final-state constraints in...

Analytic Modeling and Integral Control of Heterogeneous Thermostatically Controlled Load Populations

Ghaffari, Azad
Scott Moura
Krstic, Miroslav
2014

Thermostatically controlled loads (TCLs) account for approximately 50% of U.S. electricity consumption. Various techniques have been developed to model TCL populations. A High-fidelity analytical model of heterogeneous TCL populations facilitates the aggregate synthesis of power control in power networks. Such a model assists the utility manager to increase the stability margin of the network. The model, also, assists the customer to schedule his/her tasks in order to reduce his/her energy cost. We present a deterministic hybrid partial differential equation (PDE) model which accounts for...

Optimal Charging of Vehicle-to-Grid Fleets via PDE Aggregation Techniques

Le Floch, Caroline
Di Meglio, Florent
Scott Moura
2015

This paper examines modeling and control of a large population of grid-connected plug-in electric vehicles (PEVs). PEV populations can be leveraged to provide valuable grid services when managed via model-based control. However, such grid services cannot sacrifice a PEV's primary purpose - mobility. We consider a centrally located fleet of identical PEVs that are distributed to and collected from drivers. The fleet also provides regulation services to the grid, contracted a priori. We develop a partial differential equation (PDE)- based technique for aggregating large populations of PEVs....