Central versus localized optimization-based approaches to power management in distribution networks with residential battery storage

Significance Statement

Different approaches have been proposed previously for scheduling demand-side battery storage, usually with one of two objectives; alleviating the need for distribution grid reinforcement by managing bi-directional power flows or reducing electricity bills for customers. However, without careful coordination, the potentials of demand-side approaches might not be fulfilled.

Dr. Elizabeth Ratnam from the University of California Berkeley (formerly of the University of Newcastle, Australia) and Professors Steven Weller and Christopher Kellett from the University of Newcastle in Australia investigated two optimization-based algorithms to balance an increase in the operational savings that accrue to residential customers with combined photovoltaic (PV) battery storage systems against management of distribution grid power flows to alleviate voltage rise and other local conditions that necessitate grid reinforcement. The article was published in the International Journal of Electrical Power and Energy Systems.

The two optimization-based approaches used are a centralized quadratic program energy-shifting, where selected customers implement a distributor-specified day-ahead battery schedule and a second approach, referred to as local quadratic program energy-shifting, where distributor-specified weights are incorporated into a quadratic program-based algorithm implemented directly by customers to obtain an individual day-ahead battery charge and discharge schedule. The algorithms were applied to load and generation data from 145 Australian residential customers to investigate the customer-distributor benefits of coordinated residential battery scheduling.

The researchers introduced a modeling framework consisting of a dynamical model of a residential energy system and a distribution region described by a directed graph. Residential customers were identified in a specified region and considered ways to coordinate their day-ahead battery schedules under the assumption of a financial policy of net metering.

The two different optimization-based approaches require load and generation forecasts at different locations in the network.  Forecasting is performed by the distributor in the centralized QP case, while in the local QP case the forecasting is done at each residence.  The authors described an approach to emulate imperfect forecasts using historical data.

As a particular application of the techniques presented, the authors investigated the case where the distributor identifies its “weakest link” (via a power flow analysis), which then provides the distribution region of interest and places constraints on the optimization problems.

When assessing the benefits of residential battery scheduling with reference to a 52-week period, the baseline profile exceeded the upper limit for the edge of interest at subgraph forecast constraints of 300KW on 9 days in a year and falls below the lower limit of -150KW on 5 days in the year. It can be said that on most days, subgraph members received a reliable supply of electricity when they do not use or have a battery.

When assessing operational savings accrued to a single subgraph member (i.e., each residence) over a period of 52 weeks denoted by annual savings in $/year, it was seen that local quadratic program energy-shifting may disproportionately penalize some customers when implementing a local quadratic program-based battery schedule.  In fact, using such a localized approach resulted in a few customers seeing additional annual costs.

By contrast, the authors demonstrated that, in terms of customer benefit, the centralized quadratic program-based approach was preferable in that all customers received the same annual savings, so that no customers were penalized for utilizing battery storage.

Central versus localized optimization-based approaches to power management in distribution networks with residential battery storage. Renewable Energy Global Innovations

About the author

Elizabeth L. Ratnam received the B.E. (Hons I) degree in Electrical Engineering in 2006, and the Ph.D. degree in Electrical Engineering in 2016, both from the University of Newcastle, Australia. She subsequently held a research position with the Center for Energy Research at the University of California, San Diego. During 2001?2012 she gained engineering experience at Ausgrid, one of the largest electricity distribution networks in Australia.

Since 2016, Elizabeth has held a research position with the Berkeley Energy and Climate Institute at the University of California, Berkeley. Her research interests lie in areas that facilitate the integration of renewable energy into power systems. 

About the author

Steven R. Weller received the B.E. (Hons.I.) degree in Computer Engineering in 1988, the M.E. degree in Electrical Engineering in 1992, and the Ph.D. degree in electrical engineering in 1994, all from the University of Newcastle, Australia. During 1994?1997, he was a Lecturer in the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. In 1997, he joined the University of Newcastle, where he is currently an Associate Professor.

He served as Head of School of Electrical Engineering and Computer Science (2007-2009), and since 2013 has served as Deputy Head of the Faculty of Engineering and Built Environment. He is the recipient of an IET Control Theory and Applications Premium Award. His research interests lie in the areas of control theory and its application to energy systems and climate. 

About the author

Christopher M. Kellett received the B.Sc. in Electrical Engineering and Mathematics from the University of California, Riverside in 1997 and the M.Sc. and Ph.D. in Electrical and Computer Engineering from the University of California, Santa Barbara in 2000 and 2002, respectively.  He subsequently held research positions with the Centre Automatique et Systemes at Ecole des Mines de Paris (France), the Department of Electrical and Electronic Engineering at the University of Melbourne (Australia), and the Hamilton Institute at the National University of Ireland, Maynooth.

Since 2006, Chris has been with the School of Electrical Engineering and Computer Science at the University of Newcastle, Australia, where he is currently an Associate Professor.

A/Prof. Kellett is an Associate Editor for IEEE Transactions on Automatic Control, the European Journal on Control, and Mathematics of Control, Signals and Systems, as well as a member of the IEEE Control Systems Society Conference Editorial Board.  He has been the recipient of an Australian Research Council Future Fellowship (2011-2015), an Alexander von Humboldt Research Fellowship (2012-2013), and the 2012 IET Control Theory and its Applications Premium Award.

His research interests are broadly in the area of systems and control, with specific emphases on stability and robustness properties for nonlinear systems, high speed model predictive control, applications in electricity distribution networks, and applications in social systems such as carbon pricing and opinion dynamics.

 

 

Journal Reference

Elizabeth L. Ratnam1, Steven R. Weller2, Christopher M. Kellett 2. Central versus localized optimization-based approaches to power management in distribution networks with residential battery storage, International Journal of Electrical Power and Energy Systems 80 (2016) 396-406.

Show Affiliations
  1. Center for Energy Research, Department of Mechanical and Aerospace Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0411, USA.
  2. School of Electrical Engineering and Computer Science, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia.

 

 

Go To International Journal of Electrical Power & Energy Systems

 

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