Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)
Abstract
Commercial facility utility bills are often a strong function of demand charges -- a fee proportional to peak power demand rather than total energy consumed. In some instances, demand charges can constitute more than 50% of a commercial customer's monthly electricity cost. While installation of behind-the-meter solar power generation decreases energy costs, its variability makes it likely to leave the peak load -- and thereby demand charges -- unaffected. This then makes demand charges an even larger fraction of remaining electricity costs. Adding controllable behind-the-meter energy storage can more predictably affect building peak demand, thus reducing electricity costs. Due to the high cost of energy storage technology, the size and operation of an energy storage system providing demand charge management (DCM) service must be optimized to yield a positive return on investment (ROI). The peak demand reduction achievable with an energy storage system depends heavily on a facility's load profile, so the optimal configuration will be specific to both the customer and the amount of installed solar power capacity. We explore the sensitivity of DCM value to the power and energy levels of installed solar power and energy storage systems. An optimal peak load reduction control algorithm for energy storagemore »
- Authors:
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy Vehicle Technologies Program
- OSTI Identifier:
- 1104595
- Report Number(s):
- NREL/PO-5400-60291
- DOE Contract Number:
- AC36-08GO28308
- Resource Type:
- Conference
- Resource Relation:
- Conference: Presented at the Electrical Energy Storage Applications and Technologies (EESAT) Conference, 20 - 23 October 2013, San Diego, California; Related Information: NREL (National Renewable Energy Laboratory)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 14 SOLAR ENERGY; 25 ENERGY STORAGE; COMMERCIAL UTILITY BILLS; DEMAND CHARGE; PEAK POWER DEMAND; ENERGY STORAGE; BATTERY; DEMAND CHARGE MANAGEMENT; SOLAR POWER
Citation Formats
Neubauer, J., and Simpson, M. Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster). United States: N. p., 2013.
Web.
Neubauer, J., & Simpson, M. Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster). United States.
Neubauer, J., and Simpson, M. 2013.
"Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)". United States. https://www.osti.gov/servlets/purl/1104595.
@article{osti_1104595,
title = {Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)},
author = {Neubauer, J. and Simpson, M.},
abstractNote = {Commercial facility utility bills are often a strong function of demand charges -- a fee proportional to peak power demand rather than total energy consumed. In some instances, demand charges can constitute more than 50% of a commercial customer's monthly electricity cost. While installation of behind-the-meter solar power generation decreases energy costs, its variability makes it likely to leave the peak load -- and thereby demand charges -- unaffected. This then makes demand charges an even larger fraction of remaining electricity costs. Adding controllable behind-the-meter energy storage can more predictably affect building peak demand, thus reducing electricity costs. Due to the high cost of energy storage technology, the size and operation of an energy storage system providing demand charge management (DCM) service must be optimized to yield a positive return on investment (ROI). The peak demand reduction achievable with an energy storage system depends heavily on a facility's load profile, so the optimal configuration will be specific to both the customer and the amount of installed solar power capacity. We explore the sensitivity of DCM value to the power and energy levels of installed solar power and energy storage systems. An optimal peak load reduction control algorithm for energy storage systems will be introduced and applied to historic solar power data and meter load data from multiple facilities for a broad range of energy storage system configurations. For each scenario, the peak load reduction and electricity cost savings will be computed. From this, we will identify a favorable energy storage system configuration that maximizes ROI.},
doi = {},
url = {https://www.osti.gov/biblio/1104595},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Oct 01 00:00:00 EDT 2013},
month = {Tue Oct 01 00:00:00 EDT 2013}
}