在智慧電網架構中，需量管理系統對於電力需求方與提供方都是一個重要的概念。透過智慧電網與需求端管理，不但可以有效減少家中用電支出還能同時降低電力負載的波動性。另外，由於電動車逐漸普遍，其潛在的電力供給、電能儲存與電力共享更增加了智慧電網的可行性與能力。而當需求管理系統推及到社區時，我們設計了一個公平的電動車共享系統以節省社區的電力支出及電力附載波動。另一方面，更考慮了商辦大樓大量電動車充電之問題，提出了一個有效利用停車場電動車之電力的商辦大樓需量管理系統。本論文中，以同時考慮電動車、再生能源、電力儲存裝置之單一家庭需量管理排程最佳化為基本單位，建構出落實共享經濟之社區型雙層需量管理排程最佳化。更進一步於商辦大樓結構下，提出多量電動車充放電控制排程最佳化以降低大樓電力支出。
在實驗部分，我們請十位使用者提供他們之日常活動資料，以代表十位居住在社區之居民，並以雙層粒子群演算法求得對社區居民最有利之活動排程結果。而商辦大樓則是使用美國公開的用電資料庫，以其中美國加州某地方某日辦公大樓之用電量為基礎，進行多輛電動車之控制排程最佳化。而結果顯示，論文提出之需量管理系統，能有效的幫助社區中所有住戶降低電費支出及降低整個社區之電流負載波動。同時，在商辦大樓中亦能有效減緩多量電動車充電帶來之衝擊且有效利用電池特性，提供大樓額外的電力供給已降低電費支出與電流附載波動。

In smart grids, demand-side management (DSM) is one of the important function since it can reduce the total electricity cost of each customer, meanwhile, alleviate the aggregate peak-to-average ratio (PAR) subject to real-time pricing (RTP) policy. On the other hand, while bidirectional charging/discharging Plug-in Electric vehicles (PEV)become more general, the capability of storing electrical energy for load shifting and energy sharing among users may take smart grid to a next level. On the view point of a community, we design a fairness strategy to share PEV’s battery with neighbors to reduce
the total electricity cost and peak to average ratio (PAR). On the other hand, we try to utilize the PEVs which parked at the commercial building during working hour to fulfill part of the building’s power consumption. In our problem formulation, each home is assumed to be connected to a renewable energy resource (e.g., photovoltaic (PV) system), be equipped with an energy storage device, and have an optional PEV with the vehicle to grid (V2G) ability, and the formulation is in terms of a multi-objective optimization cooperative game to facilitate power sharing among neighbors. As for a commercial building, we rearrange each PEV’s charging/discharging operations to reduce the total
electricity cost of the building. In simulation, we ask ten people to provide their daily activity profiles to represent the residence in the community and use the hourly load profile data from Office of Energy Efficiency & Renewable Energy (EERE) for commercial sector. The results show that the proposed DSM system not only reduces the electricity cost for each household but also reduces the PAR of the community. Moreover, for the commercial building, the proper rearrangement of PEV’s behavior also helps to reduce the total electricity cost and PAR.

口試委員會審定書 i
誌謝 ii
中文摘要 iii
ABSTRACT iv
CONTENTS v
LIST OF FIGURES viii
LIST OF TABLES ix
Chapter 1 Introduction 1
1.1 Background 1
1.2 Challenges 3
1.2.1 Challenges of Utilizing the PEV 3
1.2.2 Challenges of DSM Realizing Sharing Economy in a Community 4
1.2.3 Challenges of DSM in a Commercial Building 5
1.3 Related work 6
1.4 Contribution 10
1.5 Parameters 12
1.6 Thesis organization 14
Chapter 2 Preliminaries 16
2.1 Demand Side Management 16
2.2 Particle Swarm Optimization 17
2.3 M-CHESS 20
2.4 Privacy Protection Strategy 23
Chapter 3 Community Demand Side Management Realizing Sharing Economy 25
3.1 Smart community Environment 25
3.2 System Architecture 27
3.3 Community Energy Sharing System 31
3.3.1 Input Data Profile 31
3.3.2 Individual Home Activity Scheduling 33
3.3.3 Optimization Flow 38
3.3.4 Two Level Distributed Cooperative Game 40
Chapter 4 Demand Side Management in Commercial Building Parking Space 44
4.1 Commercial building Structure 45
4.2 Systems Architecture 46
4.3 Plug-in Electricity Vehicle Operation Scheduling in Commercial Building 47
Chapter 5 System Evaluation 50
5.1 Evaluation of Residential community 50
5.1.1 Environment Setting 50
5.1.2 User Profile 53
5.1.3 Individual Home Cost Reduction 55
5.1.4 Residential Community Realizing Sharing Economy 58
5.2 Evaluation of Commercial Building with PEV Parking Space 62
5.2.1 Environment Setting 62
5.2.2 Commercial Building Cost Reduction 64
Chapter 6 Conclusions 65
6.1 Summary 65
6.2 Future Work 66
REFERENCE 67

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