Development of Simple Estimation Model for Aggregated Residential Load by using Temperature Data in Multi-Region

Abstract

With spread of photovoltaic (PV) system in power systems, it will become more difficult to keep supply-demand balance of the power in mUlti-region by control of only the system side. Cooperation between the centralized energy management and distributed energy management is important for improving the supply-demand balance. For this purpose, it is necessary to accurately forecast the load and the PV power generation in a region. However, forecasting of residential load is very difficult because of steep fluctuations. In addition, we cannot obtain every residential load data. So we need to develop a basic model that forecasts the load of mUlti-regions without using actual measured data in all of the regions.In this paper, we analyzed the main component of the load to create a load estimation model. The load response associated with temperature fluctuations was modeled per time resolution of one hour by the main component analysis. We also estimated aggregated residential loads of multi-region. On the other hand, PV power generation was chosen from a similar day based on irradiance and temperature of multi-region. As a result, a data set for large-scale power system control simulation was made, and a stable power supply from the system side will be possible by demand response (DR) using demand-side storage batteries.

Detection of Defaulting Participants of Demand Response Based on Sparse Reconstruction

“…In fact, it is known that the consumption of typical facilities providing DR service can be modeled (estimated) by decomposing the total consumption into the base consumption (unrelated to weather conditions) and consumption under weather conditions (temperature, humidity, etc.) [21]. Furthermore, the DR participants are expected to install an energy management system and in such a case the scheduled negawatt energy will be automatically generated.…”

Linear combination of day-ahead charge/discharge scheduling toward multi objective analysis of energy management system

“…For lðt; iÞ and pðt; iÞ, we employed a simulation data set for Tokyo area, Japan, 29) which had been obtained on the basis of measured data in "Demonstrative research project on gridinterconnection of clustered photovoltaic power generation system" by NEDO. 30) Therefore, lðt; iÞ and pðt; iÞ show the realistic diversity of 540 residences.…”

Day-ahead allocation of planned power flow and real-time operation method for residential houses with photovoltaic and battery for maximum use of distributed batteries

“…In this paper, we utilize the minutely estimated electrical load and PV generation in 2010, 29) which is estimated using the measured data from 540 residential houses of Ota City. The elements of temperature, attributes of a day, irradiation, and duration of sunshine were used for the estimation.…”