Clustering-based probability distribution model for monthly residential building electricity consumption analysis
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Clustering-based probability distribution model for monthly residential building electricity consumption analysis
1. State Grid (Beijing) Integrated Energy Planning and D&R Institute Co., Ltd., Beijing 100052, China 2. Building Energy Research Center, School of Architecture, Tsinghua University, Beijing 100084, China
Abstract
Keywords
Electricity is now the major form of energy used in residential buildings and has seen a significant increase in usage over the past decades. One of the main features of electricity use in residential buildings is the diversity of total electricity consumption and use patterns among households.
cluster analysis,
Current models may not be able to simulate and generate electricity use curves or reflect the variations accurately. To fill this gap, this research simulates electricity use curves in residential
electricity consumption
buildings with a clustering-based probability distribution model. The model extracts feature parameters to represent the electricity use level and patterns and then conducts a two-step cluster analysis to identify the distinctions of both electricity use levels and patterns. Based on the clustering results, probability distributions are fitted for all feature parameters within each sub-cluster. The model is then validated with three validation approaches. Monthly electricity
Research Article
Jieyan Xu1, Xuyuan Kang2, Zheng Chen1, Da Yan2 (), Siyue Guo2, Yuan Jin2, Tianyi Hao1, Rongda Jia1
probability distribution, residential building,
Article History Received: 09 May 2020 Revised: 26 July 2020 Accepted: 10 August 2020 © Tsinghua University Press and
consumption in households of the Jiangsu Province, China, was studied to test the performance
Springer-Verlag GmbH Germany,
of the model. Lastly, this paper discusses the application of this model under different spatial
part of Springer Nature 2020
resolutions and analyzes the temporal-relevant model features.
1
Introduction
E-mail: [email protected]
Building Thermal, Lighting, and Acoustics Modeling
Residential building energy use accounts for a significant amount in overall energy consumption worldwide. According to the World Energy Balances (IEA 2019a) by the IEA, the residential sector accounted for about 21.2% of the world energy in 2017. In China, buildings account for approximately 21% of the total energy consumption, while in 2017, the residential sector accounted for 23.5% of the energy consumption by buildings, excluding northern urban heating (Building Energy Research Center 2019). From 1990 to 2017, the world energy consumption in the residential sector has increased by 35% (IEA 2019b) and will keep increasing in the upcoming years (IEA 2019b). For China, the energy consumption in urban residential buildings (excluding northern urban heating) in 2015 was 199 Mtce, almost three times of that in 2001, and is still on the rise (Building Energy Research Center 2017). Major types of energy consumed by residential buildings include electricity, natural gas, LPG, solar energy, and
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