Estimating the value of jointly optimized electric power generation and end use: a study of ISO-scale load shaping applied to the residential building stock

Abstract

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.

Ten questions concerning energy flexibility in buildings

“…At the single building level, the increasing use of smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, all enhance the energy flexibility offered by buildings and can help energy systems improve operations [4,17]. At a building cluster level, inter-building cooperative energy flexibility measures have the potential to provide greater degrees of energy flexibility within a single localized operational framework [19][20][21].…”

“…In decentralized architectures, end-users share only selected information (e.g., power consumption profile) and the management strategy is decided locally. The simplest form of decentralized architecture consists of broadcasting either a price signal to end-users [35,39] or by issuing an optimal load shaping signal that buildings actively track as closely as possible by locally shaping device control strategies [19][20][21] (see Fig. 1-b).…”