Cette thèse se propose d’évaluer les produits d’effacement réalisés sur un ensemble de consommateurs, chacun étant défini par le triplet {bâtiment, systèmes, ménage}. On définit un produit d’effacement par la caractérisation de la déformation de la courbe de charge de l’ensemble des consommateurs suite à l’envoi d’un signal de contrôle (pilotage direct ou signal tarifaire).Deux dimensions ont été considérées dans le cadre de ce travail : l’étude des variables d’influence sur les effacements de consommation en s’appuyant sur des données issues d’expérimentations ainsi que l’élaboration d’un modèle global permettant de reproduire une partie de la diversité observée sur les courbes de charge des clients expérimentateurs.Afin d’analyser un échantillon {bâtiments, systèmes, ménages}, une attention particulière est portée à la dispersion des caractéristiques du bâti (enveloppes, expositions, ...) et aux éventuelles corrélations entre le ménage (mode de vie, choix des équipements, ...) et les systèmes (caractéristiques techniques), notamment pour l’usage "chauffage et climatisation".Un travail de réconciliation de données (issues de statistiques, de travaux sur la caractérisation des logements métropolitains, d’études sur les habitudes de vie des ménages, ...) a permis de proposer une première évaluation en simulation d’effacement de l’usage chauffage au périmètre d’un parc de quelques milliers de logements.L’approche bottom-up proposée permet ainsi de rendre compte de la diversité technique, fonctionnelle et d’origine comportementale de l’usage étudié. / This thesis aims at evaluating load curtailments packages over a set of electricity users, each being defined by the triolet {building, system, household}. We define a load curtailment package by the quantification of the load curve's deformation due to the emission of a control signal (direct control or price incentive).Two dimensions were considered through this work: first the study of the different variables' influence using experimental data, and secondly the construction of a global model which can effectively reproduce the diversity observed on experimental load curves.In order to analyse a sample {building, system, household}, the dispersion of the different caracteristics of the building (envelope, exposure,...) were carefully studied, as well as the possible links between the household (lifestyle, choice of household equipments,...) and the systems (technical caracteristics) especially for the electrical heaters and HVAC systems.We work to reconcile data from different sources (statistical data, data from research on urban building caracterization, on households' habits,...) and we are able to give a first evaluation of load curtailment products over the electrical heating usage in urban environment through numerical simulations of a few thousand housings. The bottom-up approach used accounts for the technical diversity, as well as the functional and behavioral diversity of the studied electrical usage.

過去電力事業為了滿足電力用戶之需求，對於新電源之開發不遺餘力。然而由於電力事業近年來在供給面規劃屢遭當地居民抗爭而受阻，因而晚近轉而強調用戶需求面之管理。 本文針對台電公司現行需求面管理之「用戶計劃性減少用電措施」四種方案進行研析。首先設定簡化條件，將四種方案予以模型化，利用經濟剩餘模型，進行邊際分析，探討台電公司提供優惠之折扣比例及電力的價格需求彈性如何參與用戶抑低容量以及消費者剩餘、生產者剩餘分配之效果。分析結果顯示：「計劃性（二）」抑低用戶負載容量最高，且參與用戶之消費者剩餘最多；「計劃性（一）」抑低用戶負載容量最低，且參與用戶之消費者剩餘最少。另一方面，若從電力公司之視角觀之，「計劃性（二）」之生產者剩餘最低，而「計劃性（一）」之生產者剩餘最高。 經濟剩餘模型分析中，由於未能充分考慮供需雙方之潛在成本與效益，因此實務上之解釋能力有其侷限之處。基於上述緣由，本文接著藉由成本效益分析，將方案實施之潛在成本與效益納入考量，分別從參與用戶之角度進行參與者檢定（Participant Cost Test, PCT）以及從電力公司之角度進行公用事業成本檢定（Utility Cost Test, UCT），以檢視不同方案在不同觀點下之績效表現。成本效益分析結果顯示：在PCT檢定下，「計劃性（四）」參與用戶之益本比最高，「計劃性（二）」參與用戶之益本比最低。而在UCT檢定下，「計劃性（一）」電力公司益本比最高，「計劃性（四）」電力公司益本比最低。將成本效益分析與經濟剩餘模型比較後可發現，用戶抑低容量高的方案對於電力公司而言未必最有利。 最後，為進一步探討關鍵變數變動造成不同方案間成本效益值之影響，因此進行敏感度分析。敏感度分析的結果顯示：若電力公司為吸引用戶而提高誘因，增加各方案給予用戶優惠折扣之比例，以參與用戶角度而言，「計劃性（四）」參與者檢定之益本比提高幅度最大；以電力公司角度而言，「計劃性（四）」公用事業成本檢定之益本比降低幅度最大。若電力公司提高參與用戶每次抑低用電負載之時數，以參與用戶角度而言，「計劃性（四）」參與者檢定之益本比降低幅度最大；以電力公司角度而言，「計劃性（四）」之公用事業成本檢定益本比提高幅度最大。 / In order to meet the users’ demand of electricity, the electric power utility spared no effort to develop the new power plant in the past. However, in recent years, the electric power utility have been hampered by local residents on supply-side planning, thus more emphasize is being put on users’ demand-side management（DSM）. This paper aims to analyze four projects of Taipower’s existing demand-side management of “incentive plan for customers’ scheduled load curtailment program”. First, we set several simplified conditions for modeling the projects. By using the economic surplus model and conducting the marginal analysis, the impact from the discount incentive provided by the utility and the elasticity of electricity price demand is explored－on participants’ load capacity reduction and the distribution of consumer surplus and producer surplus. The results of economic surplus model showed "project 2" curtails the maximum load capacity and with the highest consumer surplus; "project 1" curtails the minimum load capacity and with the lowest consumer surplus. On the other hand, in the Taipower's point of view, "project 2" provides with the lowest producer surplus while "project 1" gives the highest producer surplus. In the economic surplus model, since the potential costs and benefit were not fully considered in both supply and demand sides, several limitations exist on this model. Based on the above reasons, we utilize the cost benefit analysis, taking the potential cost and benefit into account and conducting Participant Cost Test（PCT） from the participants’ perspective and Utility Cost Test（UCT）from the utility’s perspective to examine the performance under different 4 DSM projects in different point of view. The results of cost benefit analysis showed that in the PCT test, the "project 4" comes up with the highest benefit cost ratio while "project 2" has the lowest cost benefit ratio. In the UCT test, the "project 1" has the highest cost benefit ratio while "project 4" came with the lowest cost benefit ratio. Comparing the cost benefit analysis with the economic surplus model, we could find that the project with the most load capacity reduction may not be the most favorable project for the utility. Finally, in order to further explore the key variables affecting the cost and benefit value in different projects, we simulated several scenarios for sensitivity analysis. The results of the sensitivity analysis showed that if the utility increases incentives to increase four projects’ ratio of discount for attracting participant, in the participants’ perspective, "project 4" would have the most changed rate of cost benefit ratio（increase）; in the utility's perspective, "project 4" would have the highest adjusted rate of cost benefit ratio（decrease）. If the utility increases the load curtailment duration each time, in the participants’ perspective, "project4" would have the highest adjusted rate of cost benefit ratio（decrease） ; in the utility’s perspective, " project4 " would have the highest adjusted rate of cost benefit ratio（increase）.