Evaluate Peak Usage Reduction of a Multi-round Real-time Pricing Model Using Co-simulation
Chenli Wang, Thomas Roth, Cuong Nguyen
The widespread deployment of distributed energy resources (DERs) makes energy demand and generation more dynamic than before. The most prominent existing tariffs systems, flat-rate and time-of-use (TOU), are not designed to let retail prices reflect varying power demand and supply. New dynamic pricing structures have been developed to reveal the fluctuating cost of energy so that consumers can adjust their power consumption plan based on the time-varying utility rate. However, the validation of such a real-time pricing system is still a problem since physical testing is costly and time-consuming. To address this gap, this work explores a co-simulation platform to assess the peak-shaving impact of a dynamic pricing scheme in a Transactive Energy (TE) grid.This work devised a Heating, Ventilation, and Air Conditioning (HVAC) system control strategy to adjust the heating/cooling setpoint based on utility price. To validate this price-driven algorithm, a building energy predictor was developed to predict the next-hour energy consumption based on HVAC setpoint and environment conditions. In addition, a utility simulator was also devised to publish the next two-hour energy price based on current net demand and utility capacity. All these aforementioned entities were integrated with the building simulation software, EnergyPlus, via an open-source co-simulation platform initially developed from the National Institute of Standards and Technology (NIST). The energy profiles and cost for utility were compared between a case with the proposed model and a baseline case that used the flat-rate pricing system.
May 3-6, 2022
Modeling and Simulation of Cyber-Physical Energy System
, Roth, T.
and Nguyen, C.
Evaluate Peak Usage Reduction of a Multi-round Real-time Pricing Model Using Co-simulation, Modeling and Simulation of Cyber-Physical Energy System, Milan, IT, [online], https://doi.org/10.1109/MSCPES55116.2022.9770159, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934480
(Accessed December 3, 2023)