Related Experiment Video
Updated: Oct 7, 2025
04:35
Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
Published on: July 5, 2024
2.1K
A novel method for acquiring rigorous temperature response functions for electricity demand at a regional scale
Yuki Hiruta1, Lu Gao1, Shuichi Ashina1
1Social Systems Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
The Science of the Total Environment
|January 7, 2022
Summary
Developing accurate temperature response functions (TRFs) is crucial for understanding how electricity demand impacts climate and how climate change affects energy systems. This study presents a novel method using machine learning to model these complex relationships.
Area of Science:
- Energy Systems Analysis
- Climate Change Impact Assessment
- Environmental Science
Background:
- Electricity demand influences climate through greenhouse gas emissions.
- Climate change alters electricity demand due to heating and cooling needs.
- Accurate temperature response functions (TRFs) are vital for climate and energy system projections.
Purpose of the Study:
- To develop reliable regional-scale temperature response functions (TRFs).
- To model complex electricity demand fluctuations and their relationship with temperature.
- To reduce uncertainty in climate change impact assessments on energy systems.
Main Methods:
- A novel method for acquiring TRFs was proposed, focusing on comprehensive modeling of electricity demand fluctuations.
- Six algorithms were evaluated, with multivariate adaptive regression splines (MARS) identified as the optimal choice.
- MARS was used to construct models predicting electricity demand based on multiple factors, isolating temperature's impact.
Main Results:
- The study successfully constructed models capable of precisely reproducing complex electricity demand patterns.
- The impact of temperature on electricity demand was simulated while controlling for other influencing factors.
- Temporal segments in TRFs were detected, and parameters/functional forms were determined for 10 regions in Japan.
Conclusions:
- The developed method provides a reliable approach to generating regional TRFs.
- Accurate TRFs are essential for understanding the interplay between climate change and energy demand.
- This research contributes to more precise climate projections and energy system impact assessments.
Keywords:
Climate changeElectricity demandHuman activitiesMultivariate adaptive regression splines (MARS)TemperatureTemperature response functionMore Related Videos
09:55Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
Published on: December 12, 2013
8.8K
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
10.8K
Related Concept Videos
02:44Heating and Cooling Curves
24.5K
When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
24.5K
01:23Maximum Power Flow and Line Loadability
210
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
210
01:20Maxwell-Boltzmann Distribution: Problem Solving
1.8K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.8K
01:14Temperature Measurement Sites
2.3K
A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...
2.3K
02:46Quantifying Heat
57.4K
Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a...
57.4K
01:26The Power Flow Problem and Solution
380
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk, phase angle δk, real power Pk, and reactive power Qk. Two of these four variables are inputs, while the...
380