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Stochastic Control of Smart Home Energy Management with Plug-in Electric Vehicle Battery Energy Storage and Photovoltaic Array

Wu, Xiaohua
Hu, Xiaosong
Scott Moura
Yin, Xiaofeng
Pickert, Volker
2016

Energy management strategies are instrumental in the performance and economy of smart homes integrating renewable energy and energy storage. This article focuses on stochastic energy management of a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It is motivated by the challenges associated with sustainable energy supplies and the local energy storage opportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements...

Generation Following with Thermostatically Controlled Loads via Alternating Direction Method of Multipliers Sharing Algorithm

Burger, Eric M.
Scott Moura
2017
A fundamental requirement of the electric power system is to maintain a continuous and instantaneous balance between generation and load. The intermittency and uncertainty introduced by renewable energy generation requires expanded ancillary services to maintain this balance. In this paper, we examine the potential of thermostatically controlled loads (TCLs), such as refrigerators and electric water heaters, to provide generation following services in real-time energy markets (1–5 min). Previous research in this area has primarily focused on the development of centralized control schemes with...

Optimal Component Sizing in a Two-Reservoir Passive Energy Harvesting System

Munsing, E.
Cowell, M.
Scott Moura
Wright, P.
2016

We utilize particle swarm optimization to reduce the size of the energy management components in an energy harvesting system, allowing us to eliminate the need for voltage regulators or DC-DC converters without affecting system performance. Prior literature on optimal power management in microelectronics [1, 2] has relied on engineering estimates or exhaustive parameter searches to optimize system design. No prior literature has considered the optimal design of a device with only passive components [3]. By using particle swarm optimization, we demonstrate a 55% reduction in device size...

Recursive Parameter Estimation of Thermostatically Controlled Loads via Unscented Kalman Filter

Burger, Eric M.
Scott Moura
2016

For thermostatically controlled loads (TCLs) to perform demand response services in real-time markets, online methods for parameter estimation are needed. As the physical characteristics of a TCL change (e.g. the contents of a refrigerator or the occupancy of a conditioned room), it is necessary to update the parameters of the TCL model. Otherwise, the TCL will be incapable of accurately predicting its potential energy demand, thereby decreasing the reliability of a TCL aggregation to perform demand response. In this paper, we investigate the potential of various unscented Kalman filter (...

State Estimation for an Electrochemical Model of Multiple-Material Lithium-Ion Batteries

Camacho-Solorio, Leobardo
Krstic, Miroslav
Klein, Reinhardt
Mirtabatabaei, Anahita
Scott Moura
2017

This paper presents state estimation for a system of diffusion equations coupled in the boundary appearing in reduced electrochemical models of lithium-ion batteries with multiple active materials in single electrodes. The observer is synthesized from a single particle model and is based on the backstepping method for partial differential equations. The observer is suitable for state of charge estimation in battery management systems and is an extension of existing backstepping observers which were derived only for cells with electrodes of single active materials. Observer gains still can...

A Second Order Cone Programming Model for PEV Fast-Charging Station Planning

Zhang, Hongcai
Scott Moura
Hu, Zechun
Qi, Wei
Song, Yonghua
2017

This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form service rate model of highway PEV charging stations' service abilities, which considers heterogeneous PEV driving ranges and charging demands.We utilize a modified capacitated flow refueling location model (CFRLM) to explicitly capture time-varying PEV charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM to enhance model accuracy and computational efficiency....

State-of-Charge Estimation for Lithium-Ion Batteries Based on a Nonlinear Fractional Model

Wang, Baojin
Liu, Zhiyuan
Li, Shengbo Eben
Scott Moura
Peng, Huei
2017

This paper presents a new battery state-of-charge (SOC) estimation method for lithium-ion batteries (LIBs) based on a nonlinear fractional model with incommensurate differentiation orders. A continuous frequency distributed model is used to describe the incommensurate fractional system. A Luenberger-type observer is designed for battery SOCestimation. The observer gain that can stabilize the zero equilibrium of the estimation error system is derived by Lyapunov's direct method. The proposed SOC observer is examined using the real-time experimental data of LIBs. The robustness of the...

Joint Planning of PEV Fast-Charging Network and Distributed PV Generation

Zhang, Hongcai
Scott Moura
Hu, Zechun
Qi, Wei
2017

Integration of plug-in electric vehicles (PEVs) with distributed renewable resources will decrease PEVs' well-to-wheels greenhouse gas emissions, promote renewable power adoption and defer power system investments. This paper proposes a multidisciplinary approach to jointly planning PEV fast-charging stations and distributed photovoltaic (PV) power plants on coupled transportation and power networks. First, we develop models of 1) PEV fast-charging stations; 2) highway transportation networks under PEV driving range constraints; 3) PV power plants with reactive power control. Then, we...

Battery State Estimation for a Single Particle Model With Electrolyte Dynamics

Scott Moura
Argomedo, Federico Bribiesca
Klein, Reinhardt
Mirtabatabaei, Anahita
Krstic, Miroslav
2017

This paper studies a state estimation scheme for a reduced electrochemical battery model, using voltage and current measurements. Real-time electrochemical state information enables high-fidelity monitoring and high-performance operation in advanced battery management systems, for applications such as consumer electronics, electrified vehicles, and grid energy storage. This paper derives a single particle model (SPM) with electrolyte that achieves higher predictive accuracy than the SPM. Next, we propose an estimation scheme and prove estimation error system stability, assuming that the...

Remaining Useful Life Estimation of Lithium-Ion Batteries Based on Thermal Dynamics

Zhang, Dong
Dey, Satadru
Perez, Hector E.
Scott Moura
2017

Longevity remains one of the key issues for Lithium-ion (Li-ion) battery technology. On-board Intelligent Battery Management Systems (BMS) implement health-conscious control algorithms in order to increase battery lifetime while maintaining the performance. For such algorithms, the information on Remaining Useful Life (RUL) of the battery is crucial for optimizing the battery performance and ensuring minimal degradation. However, accurate prediction of RUL remains one of the most challenging tasks until this date. In this paper, we present an online RUL estimation scheme for Li-ion...