NDLI: Synthetic residential load models for smart city energy management simulations

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Synthetic residential load models for smart city energy management simulations

Content Provider	IET Digital Library
Author	Reis, Fernando B. dos Tonkoski, Reinaldo Hansen, Timothy M.
Abstract	The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterise the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.
Starting Page	342
Ending Page	354
Page Count	13
Volume Number	3
e-ISSN	25152947
Issue Number	Issue 3, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-stg/3/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0296
Journal	IET Smart Grid
Publisher	The Institution of Engineering and Technology
Publisher Date	2020-02-25
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Coordinated Manner Customer Loads Demand Side Management Energy Management System Home Energy Management Individual Electric Assets Individual Residential Customers Known City-sized Load Curve Large-scale Residential Demand Response Load Forecasting Model Parameter Peak Demand Power Engineering Computing Power System Economics Power System Managemen Power System Operation Power System Planning And Layout Power System Simulation Power System Simulation Studies Presented Residential Queueing Load Model Queueing Theory Reduce Congestion Residential Electricity Customers Residential Load Data Smart City Energy Management Simulations Smart Power Grid Synthetic Residential Load Model System Load System-wide Electric Load Changes Time-varying Queueing Model
Content Type	Text
Resource Type	Article

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