Article Tailor-Made Feedback to Reduce Residential Electricity Consumption: The Effect of Information on Household Lifestyle in Japan

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1 Arcle Talor-Made Feedback o Reduce Resdenal Elecrcy Consumpon: The Effec of Informaon on Household Lfesyle n Japan Ako Ozawa 1, *, Ryoa Furusao 2 and Yoshkun Yoshda 2 1 Research Insue of Scence for Safey and Susanably, Naonal Insue of Advanced Indusral Scence and Technology, 16-1 Onogawa, Tsukuba, Ibarak , Japan 2 Deparmen of Envronmen Sysems, Graduae School of Froner Scences, The Unversy of Tokyo, Kashwanoha, Kashwa, Chba , Japan; furusao@globalenv.k.u-okyo.ac.jp (R.F.); y-yoshda@k.u-okyo.ac.jp (Y.Y.) * Correspondence: ako.ozawa@as.go.jp; Tel.: Academc Edor: Tomonobu Senjyu Receved: 8 December 2016; Acceped: 29 March 2017; Publshed: 30 March 2017 Absrac: Resdenal smar meerng and energy feedback have araced worldwde aenon oward reducng energy consumpon and buldng a susanable socey. Many heorecal sudes have suggesed he mporance of personalzed nformaon; however, few feedback demonsraons have focused on household lfesyle. Ths paper presens a plo program of energy feedback repors based on analycal mehods o show he relaonshp beween elecrcy consumpon and household lfesyle n Japan. One ype of repor was for households wh a ngh-orened lfesyle, whch were classfed by means of frequency analyss; was evden ha such households should shf o a healhy, envronmenally frendly, mornng-orened lfesyle. Anoher ype of repor was based on cluser analyss: pnponed he daes and mes when he household consumed much more elecrcy han wh s regular roune. Through panel daa regresson analyss, was found ha he repors conrbued o reducng daly household elecrcy consumpon as long as a boomerang effec could be avoded. I was also found ha he feedback effec was enhanced by acvaon of conscousness, norms, and moves. I was observed ha acvaon requred a good undersandng of he characerscs of elecrcy consumpon and lfesyles of each household. Keywords: resdenal elecrcy consumpon; energy feedback; lfesyle; frequency analyss; cluser analyss 1. Inroducon Recenly, smar elecrcy meerng has receved global aenon as a means of reducng power consumpon n resdenal areas. The number of smar elecrc meers nsalled worldwde wll reach 800 mllon by 2020 [1]. The sp of smar meers n Japan has been slower han n oher OECD counres; however, has been acceleraed by he full lberalzaon of he elecrcy real marke n Aprl Accordng o he fourh edon of he Sraegc Energy Plan of Japan [2], whch was he frs plan followng he caasrophc 2011 Tohoku earhquake and sunam, smar meers wll be nsalled n all Japanese households by he early 2020s. Smar meers are a crcal echnology n esablshng smar communes, whch conrbue o an energy-effcen socey by negrang nformaon and communcaon echnology (ICT) and varous energy echnologes [3]. Feedback abou elecrcy consumpon s a promsng ulzaon of elecrcy-use daa from smar meers o enhance end-users responsveness, hereby reducng her elecrcy consumpon [4]. Among praccal sudes of elecrcy feedback, varous ypes of feedback o households have Susanably 2017, 9, 528; do: /su

2 Susanably 2017, 9, of 23 been provded over recen decades [5]. Mos feedback offers nformaon on he recpens real-me or prevous elecrcy consumpon and conservaon acves; however, he effec on elecrcy conservaon dffers accordng o he approach adoped [6]. Recen sudes based on psychologcal mehods [6,7] have revealed he mporance of personalzed nformaon o ncrease household engagemen and reduce household energy consumpon. Alhough some emprcal sudes and feedback repors were conduced by power companes and publc nsues [8 10], hose sudes have no focused on household lfesyle, an mporan aspec for feedback personalzaon. Ths paper presens he fndngs from a plo program of feedback abou a household s elecrcy consumpon and s own parcular lfesyle. Here, lfesyle has a broad meanng: relaes no only o he occupans specfc behavors, e.g., sleepng, eang, and bahng, bu also o her use of home applances relaed o such behavors. To provde personalzed feedback, analyc mehods were used o denfy a household s lfesyle from s elecrcy-use daa, from whch alor-made advce o conserve elecrcy was proposed accordng o each household s lfesyle. Repors were sen o 78 households and he feedback effec for reducng household elecrcy consumpon was evaluaed by comparng he consumpon of recpens and non-recpens. Furhermore, mpressons of he repor conen were assessed by means of a quesonnare. In Secon 2 of hs paper, an overvew of he echnologcal and heorecal background relaed o feedback s provded. The analyss mehodology for resdenal elecrcy-use daa s also nroduced. In Secon 3, he dealed mehods adoped wh hs plo program are explaned. For an accurae evaluaon of he feedback effec, a sascally robus mehod usng regresson analyss for panel daa wh cluser-robus sandard errors s employed. In Secon 4, he resuls of he plo program are presened. In Secon 5, he feedback effec usng repors on conservng elecrcy s dscussed. In Secon 6, conclusons abou he plo program are offered and some polcal mplcaons are oulned. 2. Overvew of Relaed Leraure 2.1. Technologcal Background of Feedback Feedback has been developed snce he 1970s as a behavoral approach o mprovng end-use energy effcency; such feedback s provded manly hrough energy blls or repors [11 19]. Afer he ol crss, Seaver and Paerson [11] conduced a feedback expermen regardng resdenal fuel ol conservaon. They gave consumers a feedback repor abou her fuel ol consumpon rae (gallons per degree day) ha wner and her consumpon rae he prevous wner. The auhors found ha he fuel ol consumpon of he feedback group was 2.1% lower han ha of he conrol group. Hayes and Cone [12] provded energy nformaon and daly feedback nformaon abou elecrcy consumpon o four uns n a U.S. unversy suden housng complex. The resuls showed ha feedback produced an 18% reducon n average elecrcy consumpon. By conras, general nformaon decreased elecrcy consumpon by 30% nally; however, ha effec declned o 9% afer wo weeks. These resuls mply ha personalzaon s essenal o resdenal elecrcy managemen. Varous devces have been developed for he purpose of renforcng envronmenally relevan behavor [13,20 23]. In one of he earles sudes of feedback demonsraon, Selgman e al. [13] nsalled a blue lgh, whch nformed occupans ha oudoor emperaures were suffcenly low for he ar condoner o be swched off n her kchens. Ueno e al. [20] developed an advanced meerng nfrasrucure (AMI) called he onlne Energy Consumpon Informaon Sysem (ECOIS) and nsalled ECOIS n nne households n Japan. By means of a B5-sze lapop compuer dsplay, ECOIS provded he households wh he 30-mn and daly power consumpon of every applance, and proposed energy-savng acons, e.g., urnng off he TV when no one was wachng. By comparng elecrcy consumpon before and afer nsallng ECOIS, he auhors found ha households n whch ECOIS was nsalled could reduce her elecrcy consumpon by 9%. Wood and Newborough [21] developed anoher ype of AMI, called energy-consumpon ndcaors (ECIs), for he purpose of provdng feedback abou elecrcy consumpon when cookng. The auhors

3 Susanably 2017, 9, of 23 nsalled ECIs n 31 U.K. households. By comparng elecrcy consumpon beween he reamen and conrol groups before and afer ECI nsallaon, he auhors found ha 14 of he 31 households reduced elecrcy consumpon for cookng by more han 10%; sx households had savngs of over 20%. These sudes mply ha more dealed feedback s effecve n reducng household elecrcy consumpon. Followng advances n smar meerng echnologes, large-scale demonsraons usng drec feedback have ncreased snce he 1990s [24 30]. Drec feedback consues real-me nformaon abou elecrcy consumpon [24 26] or elecrcy consumpon plus prce [27 30]; s manly provded usng an n-home dsplay (IHD) [31]. However, revews of feedback demonsraons have suggesed ha real-me nformaon s no he only requremen for effecve feedback. Faruqu e al. [32] revewed 12 IHD plo programs from 1989 o 2010 n four counres (Uned Saes, Canada, Ausrala, and Japan); he auhors deermned ha households could reduce her elecrcy consumpon by 7% on average, whn a range of %. Through a revew of qualave and quanave sudes on drec feedback va IHDs, Buchanan e al. [33] found lmed evdence of he effcacy of drec feedback; he auhors mananed ha consderaon should be gven o household engagemen. In order o measure and verfy he effec of feedback repors, a few collaborave projecs have been also carred ou by uly companes and publc nsuons. For example, Pacfc Gas and Elecrc Company, an elecrc uly n he Uned Saes, sen home energy repors o he resdenal cusomers and assessed he mpac of behavoral demand response on peak elecrcy usage on four desgnaed Summer Savng Days [8]. In Japan, Jyukankyo Research Insue conduced a home energy repor plo sudy on 41,200 Hokurku Elecrc Power Company s cusomers [9]. The advce n home energy repors n he USA and Japan was made on he bass of monhly elecrcy consumpon. The Energy Demand Research Projec (EDRP) n he Uned Kngdom was carred ou o es consumers responses o dfferen forms of nformaon abou her energy use. Abou 61,300 cusomers of four Brsh power companes (EDF, E.ON, Scosh Power, and SSE) parcpaed n he EDRP, and he mpac of energy effcency advce (no personalzed o he cusomer) on annual energy reducon was measured [10] Theorecal Background of Feedback Beer undersandng of he heorecal background o he causal relaonshp beween energy consumpon and feedback s mporan for ncreasng household engagemen. Usng a psychologcal model o explan he relaonshp beween envronmenally relevan behavor and nformaon, Fscher [6] explaned how and why feedback on elecrcy consumpon conrbues o conservng elecrcy. Two processes change ndvdual habs no envronmenally frendly behavor. Termed norm acvaon, he frs process requres an ndvdual o rase hree ypes of conscousness: (1-1) conscousness of ssues; (1-2) conscousness of he relevance of he ndvdual s behavor o he ssues; and (1-3) conscousness of he ndvdual s possbles of changng her behavor. When norm acvaon s accomplshed, an ndvdual s able o underake norm evaluaon and decson makng. In he second process, dfferen behavors are evaluaed based on he followng: (2-1) personal norms; (2-2) socal norms; and (2-3) oher moves. Indvduals make hs evaluaon o choose he behavor ha maxmzes he sum of he norm values. Schulz e al. [7] suggesed ha normave nformaon can exer a dfferen effec on envronmenally relevan behavor dependng on wheher he feedback repor ndcaes wheher he recpen s behavor s above or below he norm. The auhors found ha feedback showng ha he recpen s energy consumpon was below average led o ncreased energy consumpon from baselne. In socal psychology relaed o household elecrcy consumpon, hs unnended consequence s ermed he boomerang effec. Schulz e al. also found ha he undesrable boomerang effec could be avoded by addonal messages of approval or dsapproval relaed o elecrcy consumpon. The auhors used a happy face emocon n repors o recpens whose elecrcy consumpon was below average. Opower [34] has appled hese psychologcal fndngs o s alor-made home energy repor servce n he Uned Saes. Toward acvang (2-2) socal

4 Susanably 2017, 9, of 23 norms, ha repor compared a household s elecrcy consumpon wh he average consumpon n s neghborhood. A plo program usng Opower s feedback servce found an average elecrcy-savng effec of 2.1% [35,36] Analyss Mehodology of Resdenal Elecrcy-Use Daa Advanced analyss of resdenal elecrcy-use daa s essenal for personalzaon of feedback. Varous analyss mehodologes have been developed: hey have used he regresson model [37 40]; me-seres analyss [41 49]; and cluserng echnques [46 54]. However, mos analyses have been amed a shor- and medum-erm demand forecasng; relavely few analyses have been dreced a alor-made feedback. Beckel e al. [53] adoped supervsed machne learnng echnques o esmae specfc characerscs of a household, e.g., s socoeconomc saus, dwellng, or applance sock, from s elecrcy-use daa colleced from 4232 households n Ireland. Abreu e al. [48] focused manly on he varaon n load profles n he course of a year. The auhors gahered load profles of up o 14 monhs for 15 households n Porugal and performed a cluser analyss of hose profles o denfy each household s rounes over a year. Ther analyss denfed perssen daly rounes and paerns of consumpon or baselnes ypcal for specfc weaher or daly condons, e.g., ho workng days and cold weekend days. From a power nework manager pon of vew, Espnoza e al. [49] developed a mehodology amng for boh shor-erm forecasng and cusomer profle denfcaon. They denfed egh clusers from 245 peces of hourly load daa from a HV-LV subsaon whn he Belgan grd, usng a perodc auoregresson model and a cluserng que. Jardn e al. [40] defned he represenave daly load profles by monhly elecrcy consumpon ranges and by consumers ype, from load curves of resdenal, commercal and ndusral consumers of he Ules of Elecrc Energy of São Paulo Sae, Brazl. They also presened a mehodology for he aggregaon of dfferen cusomers load profles. Ozawa e al. [47] developed wo knds of elecrcy daa analyss mehods o nvesgae relavely dealed varaons n load profles for a specfc perod of he year (for one week or one monh); he purpose was o demonsrae he relaonshp beween household elecrcy consumpon and lfesyle. Wh he frs mehod, he auhors performed a frequency analyss of he weekly load profles of ndvdual households; hey classfed 1072 households accordng o he hghes peak n he specrum dsrbuon. The households were dvded no groups based on he represenave frequences, whch were calculaed for each household. Fgure 1 shows an example of he frequency analyss. The auhors found ha he represenave frequences for over 75% of he households were a 12-h or 24-h perod. Ozawa e al. found ha he households n he 12-h group had a mornng-orened lfesyle and consumed on average 5.3% less elecrcy han households n he 24-h perod group, whch had a ngh-orened lfesyle. A mornng-orened lfesyle also has healh benefs [55 57], whch can be vewed as a (2-3) move for changng behavor. Wh he second mehod, Ozawa e al. performed a cluser analyss of each household s daly load profles o deermne he ypcal load paern. From he cluser analyses, varous load paerns and he correspondng daes for each load paern were obaned. For each household, he load paern when he household followed a regular roune for he monh was defned based on he mos common paern for ha monh. Fgure 2 shows an example of he cluser analyss. Based on an ndex evaluang he valdy of cluserng, Ozawa e al. noed ha he bes cluser analyss could be performed for each household when usng he complee lnkage mehod and wh fve clusers. They also found ha mos of he 1072 households consumed less elecrcy when hey followed a regular roune. Households can acvae her own (2-1) personal norms by reflecng on her daly lfe and elecrcy consumpon. Fgure 3 summarzes he assumed causal connecons beween norms or moves and feedback obaned hrough an analyss and comparson of household elecrcy consumpon.

5 Susanably 2017, 9, of 23 Fgure 1. Example of frequency analyss [47]. Fgure 2. Example of cluser analyss [47].

6 Susanably 2017, 9, of Maerals and Mehods 3.1. Parcpan Recrumen Fgure 3. Assumed causal connecons beween norms or moves and feedback. Parcpans for he plo program were recrued among resdens lvng n deached houses wh a home energy managemen sysem (HEMS). Wh he IHD of he HEMS, resdens can monor her real-me elecrcy consumpon and check her elecrcy consumpon records over he prevous year. Usng he HEMS, resdens are also able o swch he house s lghs and ar condoners on and off. The houses n he plo program had smlar buldng characerscs, havng been consruced afer 2011 by he same company usng he laes hea-nsulaon crera. Leers were sen o 300 households, nvng her parcpaon n he feedback plo program; posve parcpaon responses were receved from 78 households. Mos of he parcpans lved n he Kano, Chubu, or Kansa regons, whch have smlar clmae condons. Op-n plo programs such as hs end o show a beer feedback effec on reducng household elecrcy consumpon han op-ou programs [31]. An op-n mehod was chosen because such mehods are hghly recommended by research ehcs commees Elecrcy Feedback Repors and Quesonnare Feedback repors were furnshed by gaherng daa abou he 78 households elecrcy use for each 30-mn perod (kwh/30 mn) from 1 May o 30 Augus A 30-mn me nerval s he basc specfcaon requred for smar meers n Japan [58]. Elecrcy demand daa measured durng each 30-mn perod have been also used n he feedback demonsraons n Japan [20,30]. A feedback repor and a quesonnare were sen o 78 households on 28 Sepember The mehods of Ozawa e al. [47] were appled o derve he repor conen for each household from he 30-mn elecrcy demand daa of he household. Frs, a frequency analyss of he household s weekly load profle was performed. If he specrum dsrbuon of he weekly load profle showed s greaes peak wh a 24-h perod, s deermned ha he household had a ngh-orened weekly lfesyle. Conversely, f he dsrbuon dsplayed s hghes peak wh a 12-h perod, s deermned ha he household had a mornng-orened lfesyle. A ype A repor was sen o households ha sasfed he followng condons: (1) he household spen a ngh-orened lfesyle for over seven weeks n he 13 weeks from June o Augus; (2) he household spen a ngh-orened lfesyle for more han one week n he four weeks n Augus; (3) he household consumed more elecrcy han he average household n Augus. Second, for each household excep hose n he ype A group, a cluser analyss of he daly load profles n Augus was performed o classfy hem no one of fve paerns, and he ypcal load paern of he household was denfed. If he daly average elecrcy consumpon of he ypcal load paern was less han he average consumpon wh he oher paerns, a ype B repor was sen. Fnally, a ype C repor was sen o he remanng households. Fgure 4 s a flow char showng how he hree ypes of repors were sen o each household.

7 Susanably 2017, 9, of 23 Fgure 4. Flow char of household classfcaon and repor ype. Wh he quesonnare enclosed wh he feedback repor, recpens were asked abou her characerscs wh respec o personal arbues and home energy use. I should be noed ha fve of he 78 households ha receved a feedback repor faled o respond. Fgure 5a shows he composon of he recpen famles. The average numbers of famly members were as follows: all, 3.70; ype A, 3.68; ype B, 3.66; and ype C, Fgure 5b dsplays he recpen s famly ype composon: 74% of he recpens were couples wh chldren. The composon by repor ype was smlar among he recpen famles. (a) (b) Fgure 5. Recpen personal arbues: (a) number of people n he recpen s famly; (b) recpen famly ype. Fgure 6a shows he ype of energy uly; Fgure 6b presens he ype of waer heaers used n he recpen homes. Abou half of he recpens homes were all-elecrc and used elecrc heaers;

8 Susanably 2017, 9, of 23 he oher half used boh elecrcy and gas, employng gas heaers. In a comparson of households by repor ype, ype C households ended o be all-elecrc. (a) (b) Fgure 6. Recpens home energy use: (a) energy uly n recpens homes; (b) ype of waer heaer n recpens homes 3.3. Feedback Repor Conen Fgures 7 9 presen samples of he feedback repors. The feedback repor was dvded no hree areas: Comparson wh oher households, Daly elecrcy usage, and Energy-savng advce for you. Fgure 7. Sample of ype A feedback repor.

9 Susanably 2017, 9, of 23 Fgure 8. Sample of ype B feedback repor. Fgure 9. Sample of ype C feedback repor Comparson wh Oher Households Ths secon, whch s common o ype A, B, and C repors, s desgned o acvae (2-2) recpens socal norms. I provdes nformaon abou he basc feaures of a recpen s elecrcy consumpon by comparng her daly consumpon wh he average of oher recpens. The resul s summarzed n a couple of senences under he le. The fgure on he lef compares daly elecrcy consumpon n June, July, and Augus: he blue bars ndcae he recpen s daly elecrcy consumpon; he gray bars show he average consumpon of all parcpans. The graph on he rgh ndcaes all parcpans classfed no 20 groups n he order of daly elecrcy

10 Susanably 2017, 9, of 23 consumpon n Augus. The blue column ndcaes consumpon n he groups o whch he recpen belongs Daly Elecrcy Usage Ths secon enables recpens o undersand he dealed characerscs of her elecrcy usage. I does so by comparng he recpen s elecrcy profle n a parcular week or on a parcular day wh her elecrcy profle on anoher day or wh anoher household s elecrcy profle for he same perod. The conens of ype A, B, and C repors dffer from one anoher. In a ype A repor (for households wh a ngh-orened lfesyle), hs secon compares he recpen s average load profle n a week of Augus (blue bars) wh he average load profle of all parcpans n he same week (black curve). In hs way, ndcaes ha he household ends o consume consderably more elecrcy a ngh han he average household (mes wh a conspcuous gap are shown by pnk bars). In a ype B repor (for households ha consume less elecrcy when hey follow her ordnary lfesyle), hs secon compares wo of he fve load paerns obaned by cluser analyss of each household s daly load profles n Augus. One paern s he ypcal load paern: he load paern ha appears mos frequenly n ha monh (black curve). Anoher s he consumng load paern: he load paern n whch daly average elecrcy consumpon s greaes among he fve paerns (blue bars). Ths comparson pnpons he daes and mes when he household consumes subsanal amouns of elecrcy (hghlghed wh pnk bars). A ype C repor s smlar o a ype A repor: he recpen dd no consume much elecrcy a ngh Energy-Savng Advce for You Ths conen corresponds o daly elecrcy usage and dffers among he repor ypes. The advce n ype A and B repors can acvae he recpen s norms and moves. In he ype A repor, s recommended ha he recpen adops an energy-savng mornng-orened lfesyle, whch consumes less elecrcy for ar condonng and lghng a ngh. I s also suggesed ha a mornng-orened lfesyle s healhy oward acvang (2-3) oher moves. In he ype B repor, s recommended ha he recpen should reflec on her daly lfe. A reconsderaon of aspecs of daly lfe conrbues o acvang (2-1) personal norms : personal deas abou how one should ac. In he ype C repor, general ps for reducng household elecrcy consumpon are offered, e.g., unpluggng unnecessary elecrcal applances Evaluaon of Feedback Repor on Reducng Household Elecrcy Consumpon To evaluae how much household elecrcy consumpon was reduced (or perhaps ncreased) afer ng he energy feedback repor, daly elecrcy consumpon before and afer feedback need o be analyzed. John Suar Mll proposed a se of condons ha have o be me n order o demonsrae he relaonshp beween cause and effec: (1) he supposed cause has o precede he supposed effec n me; (2) he supposed cause mus correlae wh he supposed effec; and (3) oher han he cause, any oher plausble explanaons canno be denfed for he effec [31]. To confrm he causal relaonshp beween elecrcy consumpon and feedback, regresson analyss was performed for panel daa of daly elecrcy consumpon among he 87 households ha receved he feedback and he oher households, whch dd no receve. In he socal scences, dfference n dfference approaches based on panel daa regressons are commonly used o calculae he effec of reamen [31]. In Secon 3.4.1, he regresson analyss for he panel daa s presened. There are wo ypes of regresson analyss models for panel daa: he fxed effecs and random effecs models. Boh models were consruced and he valdy of each was assessed usng a sascal es. In Secon 3.4.2, usng panel daa regresson analyss, he evaluang mehod of he feedback effec on household elecrcy

11 Susanably 2017, 9, of 23 consumpon s shown. To deermne he feedback effec from among many oher facors, oher feasble explanaons, such as ousde weaher condons, were aken no accoun Regresson Analyss for Panel Daa Regresson analyss for panel daa s an analyc mehod used manly n he feld of economercs [59,60]. Suppose here are he properes of I ndvduals and T me perods for each ndvdual. For he panel daa, he mulple regresson model wh K ndependen varables can be wren as Equaon (1): 1 2 k K Y =α+β 1 +β 2 + +β k + +β K +ε =α+ bx+ε, (1) k where Y s he explaned varable of ndvdual 1, 2,, I n me perod 1, 2,, T ; s he k h k 1, 2,, K ndependen varable of ndvdual n me perod ; 1 2 k K x,,,,, s he vecor noaon of he ndependen varables; α s he nercep, whch s also ermed he ndvdual effec n he feld of panel daa analyss; β k s he parameer of k h ndependen varables; b β 1,β2,, β k,, β K 2 ε s he error erm, ε ~ N,. 0 s he vecor noaon of he parameers; and Wh he fxed effecs model, he ndvdual effec α s calculaed for each ndvdual. Therefore, f he number of me perods T s small, esmaes canno be obaned owng o he lmed degree of freedom. The random effecs model avods hs dffculy by presenng ndvdual effec α as a combnaon of he consan erm α and error erm ν. Ths sasfes he relaon n Equaon (2); however, hs model requres ha ndvdual effec are uncorrelaed: E ν 0 2 σ ( j) ν Covν,ν je νν j 0 ( j) Cov,ν j E ν j 0 α and ndependen varable k. (2) The conssency of models (fxed effecs vs. random effecs) can be evaluaed usng he Hausman es [61]. The es sasc H follows he ch-square dsrbuon wh K degrees of freedom, as shown n Equaon (3): where V ˆ bˆ fe and V bˆre 1 2 fe re V ˆ fe V ˆ bˆ bˆ bˆ bˆ re bˆ fe bˆ re ~ K H=, (3) ˆ are esmaes of he covarance marx of he esmaed parameers wh he fxed and random effecs models. If H s small, boh he fxed and random effecs models are vald. If H s suffcenly large, only he fxed effecs model s vald Evaluang Feedback Effec on Household Elecrcy Consumpon Usng Panel Daa Regresson Analyss The panel daa regresson analyss model s used o evaluae he effec of feedback. The explaned varable n he regresson analyss model was daly elecrcy consumpon of household on day Eday (kwh/day). Elecrcy-use daa from 1 May o 1 November 2015 was gahered; hus, he number of me perods T 185 ; 1 corresponded o May 1 and 185 corresponded o 1 November. Elecrcy-use daa for 78 households ha receved a feedback repor (reamen group) and 568 households ha dd no receve (conrol group) was obaned; n hs way, panel daa of he households daly elecrcy consumpon was creaed. Boh he reamen and conrol groups lved n houses wh smlar buldng characerscs and HEMSs. In he quesonnare

12 Susanably 2017, 9, of 23 enclosed wh he feedback repor, recpens were asked abou he dae when hey he repor so as o se he perod afer reamen for each recpen. The perod before he day a household he feedback s defned as before reamen and he perod on and afer ha day s defned as afer reamen. Three evaluaon mehods were underaken: lumped evaluaon, whch assessed he effec of all ypes of repors ogeher; evaluaon by repor ype, whch deermned he effec of each ype of repor; and evaluaon by household, whch assessed he effec of each ype of repor on each household. Wh lumped evaluaon, regresson analyss was performed for he panel daa of all 645 households. Wh evaluaon by repor ype and evaluaon by household, he 568 households ha dd no receve a feedback repor were classfed no hree groups accordng o he flow char n Fgure 4; panel daa was made for each group. Table 1 dsplays he number of households wh panel daa for each evaluaon. I should be noed ha owng o mssng daa, 10 of he 78 households ha receved feedback were excluded from he evaluaon. Table 1. Number of households n lumped evaluaon, evaluaon by repor ype, and evaluaon by household. Evaluaon by Repor Type Lumped Evaluaon Evaluaon by Household Type A Type B Type C # households # household whch receved a feedback repor # household whch dd no receve a feedback repor A lnear regresson model was consruced o assess he daly elecrcy consumpon of household on day Eday (kwh/day). Explanaory varables for he daly elecrcy consumpon are se based on he lnear regresson model developed by Muka e al. [30]. In order o evaluae he feedback effec on peak elecrcy demand n summer, hey chose he followng sx parameers as he explanaory varables of he lnear regresson model: he average emperaure of he peak mes, he average humdy of he peak mes, he average emperaure of he prevous hree days, a weekday dummy, an ndcaor specfyng he pos-reamen perod, and an ndcaor specfyng he pos-reamen perod by feedback ype. In hs sudy, seven explanaory varables hea humd were consdered: hree abou clmae condons (,, ); one abou weekdays or me holdays ( ); one abou change over me ( ); and wo abou feedback repors hol ( below _ average, ). hea and are varables represenng he effec of oudoor emperaure. (degree hea C) represens space ng demand and s gven by Equaon (4); (degree C) represens space heang demand and s gven by Equaon (5). Here, TEMPoa (degree C) s he daly average ousde ar emperaure on day a he prefecural capal where household was resden. These varables were based on heang and ng degree day : hese were ndces o esmae annual energy consumpon for space heang and ng. The heang and ng degrees were calculaed on a daly bass o capure daly elecrcy consumpon for space ng and heang n each household. A number of varables wh dfferen hreshold values were consdered and he mos approprae one was seleced. Boh heang and ng degrees are consdered, because he assessmen perod of hs plo program s from 1 May o 1 November. The average emperaure of he prevous hree days s excluded from explanaory varables, because has a correlaon wh hea and, whch make dffcul o oban accurae evaluaon resuls due o he mulcollneary beween a par of explanaory varables.

13 Susanably 2017, 9, of 23 TEMPoa 24 ( TEMPoa 24) (4) 0 ( TEMPoa 24) hea 14 TEMPoa ( TEMPoa 14) (5) 0 ( TEMPoa 14) humd [%] s he daly average humdy on day a he prefecural capal where household was resden. hol hol s a dummy varable represenng wheher day was a weekday ( 0 ) or holday ( hol 1 ). Holdays are Saurdays, Sundays, and naonal holdays: n 2015, 4 6 May, 20 July, Sepember, and 12 Ocober. Ths varable corresponds o he weekday dummy n he lnear regresson model developed by Muka e al. [30]. me s a dummy varable represenng change n household elecrcy consumpon over me. Ths dummy varable s se o remove me-dependen nfluences excep clmae condon. me 1 f day was afer 30 Sepember when households receved feedback repors, and me 0 f was before 29 Sepember. Ths varable corresponds o he ndcaor specfyng he pos-reamen perod n he lnear regresson model developed by Muka e al. [30]. s a dummy varable represenng feedback effec on household elecrcy consumpon. Le be he dae when household a feedback repor. 1 f day was afer he followng day of ( ); 0 f day was before ( ) or he household dd no receve a feedback repor. Ths varable corresponds o he ndcaor specfyng he pos-reamen perod by feedback ype n he lnear regresson model developed by Muka e al. [30]. _ average s a dummy varable represenng he boomerang effec of he feedback repor on below household elecrcy consumpon. If consumpon n Augus was below he average, he repor saed, In Augus, you consumed (consderably) less elecrcy han he average household n he Comparson wh oher households secon. Of 68 households, 31 receved such a repor: egh households receved ype A; 17 households receved ype B; and sx households receved ype C. below _ average 1 f day s he nex day afer ( ) and he repor saed, In Augus, you below _ average consumed (consderably) less elecrcy han he average household. Oherwse, 0. Wh lumped evaluaon and evaluaon by repor ypes, wo lnear regresson models composed by he above explanaory varables s assumed. Wh he sx-varable model, Equaon (6), he oal effec of all conen n he repor ( ) on household elecrcy consumpon could be evaluaed. Wh he seven-varable model, Equaon (7), he boomerang effec of he message, In below _ average Augus, you consumed (consderably) less elecrcy han he average household ( ) and he feedback effec of he oher nformaon ( ) on household elecrcy consumpon could be separaely assessed. To avod an naccurae evaluaon resul caused by heeroscedascy and auocorrelaon n he models, cluser-robus sandard errors were calculaed usng Thompson s mehod [62] and ha of Cameron e al. [63]: Eday (6) hea hea humd humd hol hol me me Eday hea hea humd humd hol hol me me eff below_ average. (7) For evaluaon by household, a lnear regresson model s gven by Equaon (8). esmaed usng he feedback effec on household s elecrcy consumpon: s Eday hea hea humd humd hol hol me me. (8)

14 Susanably 2017, 9, of 23 To deermne whch household was mos nfluenced by a ype B feedback repor, a regresson analyss beween he feaures of households elecrcy consumpon and he feedback effec was performed. The regresson formula s gven n Equaon (9), where Eday yp (kwh/day) s he daly average elecrcy consumpon of a ypcal load paern n Augus, Eday mos (kwh/day) s he daly average elecrcy consumpon of a consumng load paern n Augus, and R Eday mos Eday s he rao of elecrcy consumpon of he ypcal load paern and yp consumng load paern: ˆ Eday Eday R. (8) B Eyp yp Emos mos R 4. Resuls 4.1. Recpens Impressons of he Repor Wh he quesonnare enclosed wh he feedback repor, recpens were asked for her mpressons of he repor. From he quesonnare responses, was found ha mos households found he repor benefcal. Respondng o he queson as o wheher he repor was useful, 86% of recpens answered n he affrmave. Ths resul underlnes he appropraeness of alor-made feedback for many households n addon o he monorng of real-me elecrcy consumpon hrough he IHD. I should be noed ha he parcpans n hs op-n demonsraon plo program ended o have hgh neres n he feedback repor. The recpens favorable mpresson of he feedback would appear o reflec her nclnaon o follow he advce. Responses o he queson as o wheher recpens followed energy-savng advce ndcaed ha abou 70% of recpens ndcaed wllngness o do so Evaluaon of Feedback Repor on Reducng Household Elecrcy Consumpon Daly Average Elecrcy Consumpons of Treamen and Conrol Groups Fgure 10 shows he comparson resuls of he daly average elecrcy consumpon of he reamen and conrol groups before he feedback (June o Augus 2015); he elecrcy consumpon of he wo groups was smlar. Fgure 10. Daly average elecrcy consumpon of he reamen and conrol groups.

15 Susanably 2017, 9, of Lumped Evaluaon The elecrcy-savng effec was evaluaed for all he repor ypes usng he elecrcy daa of 636 households (68 receved a feedback repor; 568 dd no). Table 2 shows he correlaon coeffcens of he explanaory varables. The par of varables wh he sronges correlaon was below _ average and (+0.67): boh were dummy varables represenng he feedback effec. The oher pars had a weak correlaon ( 0.30 o +0.30) Table 2. Correlaon coeffcens of he explanaory varables. hea humd hol me below _ average hea humd below hol me _ average Table 3 presens he resul of he regresson analyss for he fxed effecs and random effecs models wh sx explanaory varables (Equaon (6)). Wh boh models, he daly elecrcy consumpon of a household ncreased sgnfcanly when he oudoor emperaure was hgh ( ) hea humd hol or low ( ), when he oudoor humdy was hgh ( ), and on holdays ( ). However, daly elecrcy consumpon ncreased, hough no sgnfcanly, afer he household he feedback repor ( ). The wo models had almos he same values of esmaed coeffcens. Tha s because he number of evaluaon me perods was suffcenly large o perform regresson analyss for he panel daa. The resul of he Hausman es ndcaes ha boh models were vald. Table 3. Resul of regresson analyss (sx varables, lumped). Fxed Effec Model Random Effec Model Coeffcens Sandard Errors Coeffcens Sandard Errors *** *** hea *** *** humd *** *** hol *** *** me Adj. R-squared Hausman es Null hypohess s rue. (Boh models are vald.) *** p < Table 4 shows he resul of he regresson analyss for he fxed effecs and random effecs models wh seven explanaory varables (Equaon (7)). As wh he resul of he regresson analyss hea model wh sx explanaory varables, he varables for oudoor emperaure (, ), oudoor humd hol humdy ( ), and holday ( ) sgnfcanly conrbued o ncreased daly household elecrcy consumpon. Regardng he effec of feedback repors, daly elecrcy consumpon ncreased sgnfcanly afer a household he message In Augus, you consumed below _ average (consderably) less elecrcy han he average household from he repor ( ). Whou hs effec, household elecrcy consumpon decreased by kwh/day (based on he fxed effecs model) afer ng he feedback repor ( ); ha s equvalen o a 3.22% reducon n

16 Susanably 2017, 9, of 23 daly average consumpon for all households from June o Augus. Boh he fxed effecs and random effecs models showed almos he same resuls. The resul of he Hausman es ndcaed ha he resul of he fxed effecs model should be appled. Table 4. Resul of regresson analyss (seven varables, lumped). Fxed Effecs Model Random Effecs Model Coeffcens Sandard Errors Coeffcens Sandard Errors *** *** hea *** *** humd *** *** below hol *** *** me _ average *** *** Adj. R-squared Hausman es Null hypohess s false. (Only fxed effec model s vald) *** p < Evaluaon by Repor Type The elecrcy-savng effec was deermned accordng o each repor ype. Wh he lumped evaluaon, here was lle dfference beween he esmaed coeffcens of he fxed effecs and hose of he random effecs model; ha was because he evaluaon perod was suffcenly long ( T 185 ). In addon, n he case of he lumped evaluaon usng he seven-varable model, he Hausman es ndcaed ha only he fxed effecs model was vald. Accordngly, he resuls for ha model are presened. below _ average Fgures 11 and 12 show he coeffcens of and esmaed for each repor ype (full ses of he regresson analyss resuls appear n Appendx A Tables A1 A3). Wh each _ average repor ype, he esmaed coeffcen of was posve: ype A, kwh/day; ype B, below kwh/day; and ype C, kwh/day. Wh regard o feedback effec, he coeffcens of esmaed from he seven-varable model were all negave. The greaes mpac was shown by ype A. The dfference n household elecrcy consumpon before and afer he feedback wh ype A was kwh/day: a 5.76% reducon n daly average consumpon of ype A households from June o Augus, when he repor dd no sae In Augus, you consumed (consderably) less elecrcy han he average household. The feedback effecs of ypes B and C whou he boomerang effec were, respecvely, kwh/day and kwh/day. When comparng he reducon raes per daly average consumpon, he feedback effec of ype B ( 0.74 %) was wce ha of ype C ( 0.37 %). The coeffcen of wh ype A esmaed from he sx-varable model was also negave. Household elecrcy consumpon decreased afer he household a ype A repor. Fgure 11. Coeffcens of (fxed effecs model).

17 Susanably 2017, 9, of 23 Fgure 12. Coeffcens of below _ average (fxed effecs model) Evaluaon by Household The resul of he elecrcy-savng effec was deermned for each household ha receved a ype B repor. Table 5 shows he regresson analyss resul of he feedback effec on each household for ha repor. The esmaed coeffcens of Eday yp and R were sgnfcanly negave. Ths resul suggess ha a household decreased s elecrcy consumpon upon recevng a ype B repor f s daly average elecrcy consumpon wh he ypcal load paern before he feedback was hgh and he consumpon of he consumng load paern was much hgher han ha of he ypcal load paern. 5. Dscusson Table 5. Regresson analyss resul (ype B). Coeffcens Sandard Errors ** Eday yp ** Eday mos R * Adj. R-squared F sas ** * p < 0.10; ** p < The plo program produced fndngs abou he effec of feedback on a household s elecrcy consumpon and s lfesyle. The resuls ndcae ha he acvaon of conscousness, norms, and moves based on nformaon abou household lfesyle has an nfluence on he feedback effec. In parcular, he resuls emphaszed he mporance of (2-3) oher moves. The evaluaon resul by repor ype suggess ha a ype A repor has a greaer effec on household elecrcy consumpon han he oher ypes. A ype A repor was sen o households ha ended o spend a ngh-orened lfesyle. From a comparson of he household s average load profle n a week and he average load profle of all parcpans durng he same week, he ype A repor poned ou ha he household ended o consume much more elecrcy a ngh han he average household. From a ype A repor, recpens receved advce ha hey should aemp an energy-savng mornng-orened lfesyle wh less elecrcy consumpon for ar condonng and lghng a ngh. The repor also saed ha a mornng-orened lfesyle s also desrable n erms of he recpens healh [55 57] oward acvang (2-3) oher moves for behavoral changes. The evaluaon resul by repor ype mples ha (2-3) oher moves encouraged reducon n elecrcy consumpon. A ype B repor also produced a endency o save elecrcy, bu he magnude was smaller han wh ype A. A ype B repor was sen o households ha consumed less elecrcy when hey followed her ordnary lfesyle. From a comparson beween he household s daly load profle wh he ypcal load paern and ha of he consumng load paern, he ype B repor pnponed

18 Susanably 2017, 9, of 23 he daes and mes when each household consumed much more elecrcy han wh s ordnary lfesyle. Ths feedback helped recpens reflec on her daly lfe and fnd some causes of a spke n elecrcy usage, oward acvang he recpens own (2-1) personal norms. The evaluaon resul by repor ype ndcaes ha he average feedback effec wh ype B was mnue. However, he resul by household suggess ha a household decreased s elecrcy consumpon f s daly average elecrcy consumpon wh he ypcal load paern before he feedback was hgh and he consumpon n he consumng load paern was much hgher han ha of he ypcal load paern. These resuls mply ha nformaon abou major dfferences beween he ypcal load paern and consumng load paern encouraged recpens o acvae her personal norms, hereby reducng her elecrcy consumpon. The followng pons should be noed for fuure research. I s mporan o develop a mechansm ha avods unnended consequences, such as he boomerang effec. The resuls of he lumped evaluaon wh seven explanaory varables (Table 4) ndcae ha daly elecrcy consumpon ncreased sgnfcanly afer a household he message In Augus, you consumed below _ average (consderably) less elecrcy han he average household from he repor ( ); hs effec was sronger han he oher effec ( ). Some expermenal sudes have addressed he conrol of such unnended consequences [7,35,36], and hey found ha addng an njuncve componen o he message could reduce he boomerang effec. Well-desgned mehods of provdng nformaon can enhance he effec of alor-made feedback. The use of varous sensor echnologes and advanced daa analyss echnologes should also be advanageous n mprovng feedback. Wh hs plo program, aggregaed elecrcy load profles were analyzed o denfy household lfesyles. More dealed feaures of he resdens behavor could have been nvesgaed f elecrcy-use daa for each applance could have been obaned. I may be expeden o measure resdens qualy of lfe by collecng her physcal daa usng wearable devces. Improvemens n he daa analyss mehod are also mporan for praccal alor-made feedback. Two analyc mehods (frequency analyss and cluser analyss) were used o deec he feaures of resdenal load profles. An advanced analyc mehod, such as deep learnng, should be employed n fuure o deal wh massve daa on energy consumpon. Inegrang analyss echnologes and sensor echnologes wll become ncreasngly mporan. I s also essenal o conduc a large-scale expermen for wde applcaon of he feedback. Owng o he delay n he sp of smar meers n Japan, he avalable elecrcy-use daa here a presen are scan compared wh oher OECD counres. Implemenng a long-erm feedback plo program wh many parcpans would show he scale effec and prolonged effec of he feedback. 6. Conclusons Usng energy feedback repors based on elecrcy-use daa analyss mehods, he feedback effec on household elecrcy consumpon was evaluaed n hs paper. In a repor based on he resuls of frequency analyss (ype A), he recpen s load profle n a week n Augus was compared wh he average load profle of all parcpans durng he same week: s ndcaed ha he recpen consumed more elecrcy a ngh han he average household. The average feedback effec was kwh/day wh he boomerang effec and kwh/day whou he boomerang effec. In a repor based on he resuls of cluser analyss (ype B), he ypcal load paern and consumng load paern of each household were compared: s saed ha recpens consumed less elecrcy when hey followed her own ordnary lfesyle. The average feedback effec here was kwh/day wh he boomerang effec and kwh/day whou he boomerang effec. Recpens sgnfcanly reduced her elecrcy consumpon f her daly average elecrcy consumpon wh he ypcal load paern before he feedback was hgh and her daly average elecrcy consumpon wh he consumng load paern was hgher han ha of he ypcal load paern. From a quesonnare survey on he feedback repors, s found ha alor-made feedback was benefcal for over 80% of recpens. For he purposes of demand-sde managemen, he Japanese governmen has requred ha power companes nsall smar meers n all households by he early 2020s. However, few sudes

19 Susanably 2017, 9, of 23 have examned feedback abou a household s energy consumpon and s own lfesyle [2]. Ths plo program usng alor-made feedback demonsraed how o promoe energy-conservaon measures among Japanese resdens, whch hhero has been nsuffcenly developed. In hs plo program, s found ha alor-made feedback correspondng o a household s lfesyle s necessary among many households. I s also found ha hs feedback had an effec on reducng elecrcy consumpon. Acknowledgmens: We acknowledge he cooperaon and advce gven by Msawa Homes Insue of Research and Developmen Co., Ld. Auhor Conrbuons: Ako Ozawa and Ryoa Furusao desgned he feedback plo and carred ou. Ako Ozawa evaluaed he feedback effecs and drafed he manuscrp. Yoshkun Yoshda conceved of he sudy and helped draf he manuscrp. Conflcs of Ineres: The auhors declare no conflc of neres. Appendx A Table A1. Regresson analyss resul (fxed effecs model, ype A). Sx Varables Seven Varables Coeffcens Sandard Errors Coeffcens Sandard Errors *** *** hea *** *** humd *** *** below hol *** *** me _ average *** Adj. R-squared *** p < Table A2. Regresson analyss resul (fxed effecs model, ype B). Sx Varables Seven Varables Coeffcens Sandard Errors Coeffcens Sandard Errors *** *** hea *** *** humd *** *** below hol ** ** me _ average Adj. R-squared ** p < 0.05; *** p < Table A3. Regresson analyss resul (fxed effecs model, ype C). Sx Varables Seven Varables Coeffcens Sandard Errors Coeffcens Sandard Errors *** *** hea *** *** humd *** *** 0.005

20 Susanably 2017, 9, of 23 below hol me _ average Adj. R-squared *** p < Nomenclaure Subscrp Un Descrpon Household Dae when household a feedback repor Regresson Parameer Un Descrpon α α ν Day Inercep (ndvdual effec) 2 σ ν Varance of he error erm β k (kwh/day)/degree C hea (kwh/day)/degree C humd (kwh/day)/% hol kwh/day me kwh/day kwh/day eff kwh/day ˆ B kwh/day Eyp Emos R b bˆ fe bˆ re V ˆ bˆ fe ˆ V bˆre 2 ε Error erm, ~ N, Consan erm of ndvdual effec, used n he random effecs model Error erm of ndvdual effec, used n he random effecs model ν Parameer of k h ndependen varables Parameer of explanaory varable represenng space ng demand Parameer of explanaory varable represenng space heang demand Parameer of explanaory varable represenng daly average humdy Parameer of dummy varable represenng wheher day was a weekday or holday Parameer of dummy varable represenng change n household elecrcy consumpon over me Parameer of dummy varable represenng feedback effec on household elecrcy consumpon Parameer of dummy varable represenng he boomerang effec of he feedback repor on household elecrcy consumpon Esmaed parameer of dummy varable represenng feedback effec of a ype B repor on elecrcy consumpon of household Parameer of daly average elecrcy consumpon of a ypcal load paern n Augus Parameer of daly average elecrcy consumpon of a consumng load paern n Augus Parameer of rao of elecrcy consumpon of he ypcal load paern and consumng load paern Vecor noaon of he parameers Vecor noaon of he esmaed parameers wh he fxed effecs model Vecor noaon of he esmaed parameers wh he random effecs model Covarance marx of he esmaed parameers wh he fxed effecs model Covarance marx of he esmaed parameers wh he random effecs model 2 Varance of he error erm H Hausman es sasc Regresson Varable Un Descrpon Eday kwh/day Daly elecrcy consumpon Eday Daly average elecrcy consumpon of a ypcal load paern n yp kwh/day Augus Eday mos kwh/day Daly average elecrcy consumpon of a consumng load paern n Augus ε 0 ε

21 Susanably 2017, 9, of 23 Rao of elecrcy consumpon of he ypcal load paern and R consumng load paern TEMPoa degree C Daly average ousde ar emperaure x Vecor noaon of he ndependen varables k kh ndependen varable (explanaory varable) degree C Explanaory varable represenng space ng demand hea degree C Explanaory varable represenng space heang demand % Explanaory varable represenng daly average humdy humd hol me below Y _ average Dummy varable represenng wheher day was a weekday or holday Dummy varable represenng change n household elecrcy consumpon over me Dummy varable represenng feedback effec on household elecrcy consumpon Dummy varable represenng he boomerang effec of he feedback repor on household elecrcy consumpon Explaned varable References 1. Telefónca. The Smar Meer Revoluon. Towards a Smarer Fuure. Avalable onlne: hps://o.elefonca.com/mulmeda-resources/he-smar-meer-revoluon-owards-a-smarer-fuure (accessed on 29 March 2017). 2. Agency for Naural Resources and Energy. 4h Sraegc Energy Plan; Agency for Naural Resources and Energy: Tokyo, Japan, Agency for Naural Resources and Energy. ANRE s Inaves for Esablshng Smar Communes; Agency for Naural Resources and Energy: Tokyo, Japan, Heskanen, E.; Johnson, M.; Vadovcs, E. Learnng abou and nvolvng users n energy savng on he local level. J. Clean. Prod. 2013, 48, Delmas, M.A.; Fschlen, M.; Asenso, O.I. Informaon sraeges and energy conservaon behavor: A mea-analyss of expermenal sudes from 1975 o Energy Polcy 2013, 61, Fscher, C. Feedback on household elecrcy consumpon: A ool for savng energy? Energy Effc. 2008, 1, Schulz, P.W.; Nolan, J.M.; Caldn, R.B.; Goldsen, N.J.; Grskevcus, V. The Consrucve, Desrucve, and Reconsrucve Power of Socal Norms. Psychol. Sc. 2007, 18, Pacfc Gas & Elecrc Company. Behavoral De mand Response Sudy Load Impac Evaluaon Repor. Avalable onlne: hp:// (accessed on 29 March 2017). 9. Hrayama, S. Home Energy Repor Plo: Large-scale look a consumer behavor n Japan. In Proceedngs of he BECC 2016 Conference, Balmore, MD, USA, 21 Ocober Offce of Gas and Elecrcy Markes (OFGEM). Energy Demand Research Projec Fnal Analyss. Avalable onlne: hps:// (accessed on 29 March 2017). 11. Seaver, W.B.; Paerson, A.H. Decreasng fuel-ol consumpon hrough feedback and socal commendaon. J. Appl. Behav. Anal. 1976, 9, Hayes, S.C.; Cone, J.D. Reducng resdenal elecrcal energy use: Paymens, nformaon, and feedback. J. Appl. Behav. Anal. 1977, 10, Selgman, C.; Darley, J.M.; Becker, L.J. Behavoral approaches o resdenal energy conservaon. Energy Buld. 1978, 1, Ble, R.G.; Valesano, R.; Thaler, G. The Effecs of Daly Cos Feedback on Resdenal Elecrcy Consumpon. Behav. Modf. 1979, 3, Nelsen, L. How o ge he brds n he bush no your hand. Energy Polcy 1993, 21, Wlhe, H.; Lng, R. Measured energy savngs from a more nformave energy bll. Energy Buld. 1995, 22,