Abstract-This paper provides new regression models for demand reduction of Demand Response programs for the purpose of ex ante evaluation of the programs and screening for recruiting customer enrollment into the programs. The proposed regression models employ load sensitivity to outside air temperature and representative load pattern derived from cluster analysis of customer baseline load as explanatory variables.The proposed models examined their performances from the viewpoint of validity of explanatory variables and fitness of regressions, using actual load profile data of Pacific Gas and Electric Company's commercial and industrial customers who participated in the 2008 Critical Peak Pricing program including Manual and Automated Demand Response.
The California energy crisis of 2000," like a bomb exploding in a crowd, alerted the world to the issues surrounding safe and secure energy supply. Increasing energy demand calls for an expanding supply system in order to realize a stable supply of energy. On the other hand, environmental problems such as global warming, the heat island phenomenon, resource depletion, and so on, call for a more effi cient and energysaving supply system. With these as a background, load leveling, one of the effects of DSM (Demand Side Management), is considered to be an effective method. In this paper, 24-hour investigations on SOHO (Small Office Home Office), residential buildings and offices were conducted in the central Tokyo area. Based on the results, the monthly and hourly energy consumption characteristics of SOHO were ascertained. In addition, the dimensionless parameters, load leveling ratio r l and energy saving rate r s were defi ned. Using r l , SOHO was proven to have profound effects on load leveling; and using r s , the energy saving potential was evaluated quantitatively.
In order ω bu皿d a 3table and energy ・ saving supply system , it is important敦) e8tabli8h databases of energy demand 最》 r various buildings , With the popularity Qf the Internet , the diversi 丘ed employment patterns , and the change80f li { b style , SOHO ( Small OMoe Home Office ) has increased signi 五cantly in the past few years in the central Tbkyo area . A8 a new kind of architecture , the energy consumption study on SOHO in urban center area has not been conducted yet . This study aims to clarify the correlation between energy oDnsumption and Iife 3tyle of u8ers , as weU as to establish an energy oon3umption database of SOHO in urban center , which will serve as a baseline when such a building is de8igned . For this purpo8e , investigation8 on SOHO were conducted in the central ? ) kyo area . Based on the results , the databa8e ofenergy oonsumption basic unit was established , And the value of a 且 nual energy consumption of SOHO was 1712. 9MJ1 (m2 ・ annuaD , which was between dwelling heuse and ollice . The life style efeach user has a great inipact on energy consumption both in value and in pattern . The results also show the importance of taking control ofindividual energy censumption .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.