Journal
JOURNAL OF BUILDING PERFORMANCE SIMULATION
Volume 15, Issue 4, Pages 507-535Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/19401493.2021.1998222
Keywords
Co-optimization of generation and residential electric load; optimum electric load shaping; model predictive control; demand response; demand side management
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Funding
- U.S. Department of Energy (DOE) [DE-AC36-08GO28308]
- U.S. Department of Energy Office of Energy Efficiency and Renewable Energy
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This study examines the impact of joint optimization of electric power generation and flexible end uses on production costs and CO2 emissions to support increasing penetrations of renewable energy. Results indicate that a transaction-less yet continuous demand response system can reduce production costs and CO2 emissions by encouraging Internet-connected devices to autonomously explore options to favor lowest cost generators.
A generation-to-load simulation estimated the impact, in terms of production costs and CO2 emissions, attributable to the joint optimization of electric power generation and flexible end uses to support increasing penetrations of renewable energy. Newly conceived, evaluated, and foundational in developing a U.S. National Standard was a transaction-less yet continuous demand response system based on a day-ahead optimum load shape (OLS) designed to encourage Internet-connected devices to autonomously and voluntarily explore options to favour lowest cost generators - without requiring two-way communications, personally identifiable information, or customer opt-in. Boundary conditions used for model calibration included historical weather, residential building stock construction attributes, home appliance and device empirical operating schedules, prototypical power distribution feeder models, thermal generator heat rates, startup and ramping constraints, and fuel costs. Results of an hourly-based annual case study of Texas indicate a 1/3 reduction in production costs and a 1/5 reduction in CO2 emissions are possible.
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