The smart grid paradigm provides a two-directional communication between the homeowner and the electric utility, to exchange information regarding energy consumption for the benefit of both parties. This capability has attracted research efforts in combining demand side management-based game theoretic optimization frameworks. These frameworks usually consist of several rounds of optimization, where several messages are being sent back and forth between the smart meter and the electric utility, most likely, over the Internet. However, no research efforts have been conducted on observing the potential impact that these bulk of messages may have over the infrastructure needed by the utility company to process these data transactions, possibly, all at once. On this regard, we propose a fog computing and smart gateway implementation for demand side management-based game theoretic frameworks in order to diminish this potential impact. This implementation can process local energy loads and report the outcome to the utility company, or one of its representatives for servicing purposes.

智能電網的模式提供了房主和電力公司之間的雙向溝通，對於能源消耗雙方的利益交換信息。這種能力吸引了組合的管理需求方博弈論優化框架的研究工作。這些框架通常由多輪優化，其中一些郵件被來回傳送的智能電錶和電力之間，最有可能的，在互聯網上的。然而，沒有研究工作已在觀察可能產生的影響進行了這些群發郵件可能比由電力公司來處理這些數據的交易，可能需要的基礎設施，全部一次。在這方面，我們提出了一個大霧計算和智能網關實施的管理需求方博弈論框架，以減少這種潛在影響。此實現可以處理當地的能源負荷和結果報告給公用事業公司，或其代表為服務宗旨。

Contents
Abstract iii
Acknowledgements iv
List of Figures vii
List of Tables viii
1 Introduction 1
1.1 Key concepts used in our work........................ 1
1.2 Purpose of this work ............................. 6
2 Our user constraint-based game theoretic framework... 8
2.1 Our game theoretic framework ........................ 8
2.1.1 Power system model ......................... 8
2.1.2 Energy cost function ......................... 9
2.1.3 Load control on consumer end.................... 10
2.2 Players..................................... 10
2.2.1 Power company............................ 10
2.2.2 Consumers .............................. 10
2.3 Constraints for appliances and users ..................... 12
2.4 Strategy of the user .............................. 14
2.4.1 Users’ objective function....................... 14
3 Proposed fog computing and smart gateway game theoretic implementation 16
3.1 System architecture.............................. 16
3.2 Workflow of our game theoretic framework on the proposed system archi-
tecture. .................................... 16
3.2.1 Algorithms .............................. 17
4 Description of test bed and results 21
4.1 Software and frameworks used......................... 21
4.2 Software models of neighborhood, houses and appliances . . . . . . . . . . 21 4.2.1 Software modeled houses ...................... 21
4.3 Electric utility/Distribution center ...................... 23
4.4 Networking .................................. 23
4.4.1 WebSocket.............................. 24
4.5 Hardware used ................................ 24
4.5.1 HouseAgent’s hardware ....................... 24
4.5.2 FogAgent’s hardware......................... 24
4.5.3 Electric utility’s hardware ...................... 25
4.6 Physical locations used ............................ 25
4.7 Workflow of testbed.............................. 27
4.8 Results..................................... 30
4.8.1 Fog computing and smart gateway benchmarks . . . . . . . . . . . 30
4.8.2 Data transmitted and received .................... 31
4.8.3 Total system time........................... 31
5 Comparison between a traditional smart grid implementation 32
5.1 Comparison between implementations.................... 33
5.1.1 Comparison of avg. time and total system time. . . . . . . . . . . . 34
5.2 Discussion................................... 35
5.2.1 Response roundtrip ......................... 35
5.2.2 Data received and transmitted .................... 35
5.2.3 Total system time........................... 37
5.3 Others..................................... 37
6 Conclusions
A Resources of the implementation References
38 40 41

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