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Renewable Energy Source in Home


Affiliations
1 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
2 Arunkumar is with the Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
3 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
     

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A smart community is a distributed system consisting of a set of smart homes which utilize the smart home scheduling technique to enable customers to automatically schedule their energy loads targeting various purposes such as electricity bill reduction. Smart home scheduling is usually implemented in a decentralized fashion inside a smart community, where customers compete for the community level renewable energy due to their relatively low prices. Typically there exists an aggregator as a community wide electricity policy maker aiming to minimize the total electricity bill among all customers. This paper develops a new renewable energy aware pricing scheme to achieve this target. We establish the proof that under certain assumptions the optimal solution of decentralized smart home scheduling is equivalent to that of the centralized method, reaching the theoretical lower bound of the community wide total electricity bill. In addition, an advanced cross entropy optimization technique is proposed to compute such a pricing scheme, which is also integrated with smart home scheduling. The simulation results demonstrate that our pricing scheme facilitates the significant reduction of both the community wide electricity bill and individual electricity bills compared to the state-of-the-art smart home scheduling technique. In particular, the community wide electricity bill can be reduced to only 0.06% above the theoretic lower bound.


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Abstract Views: 244

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  • Renewable Energy Source in Home

Abstract Views: 244  |  PDF Views: 4

Authors

S. Jegan
Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
U. L. Arunkumar
Arunkumar is with the Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
M. Kowsapandian
Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
S. Prabhakaran
Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India
R. Santhoshkumar
Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, India

Abstract


A smart community is a distributed system consisting of a set of smart homes which utilize the smart home scheduling technique to enable customers to automatically schedule their energy loads targeting various purposes such as electricity bill reduction. Smart home scheduling is usually implemented in a decentralized fashion inside a smart community, where customers compete for the community level renewable energy due to their relatively low prices. Typically there exists an aggregator as a community wide electricity policy maker aiming to minimize the total electricity bill among all customers. This paper develops a new renewable energy aware pricing scheme to achieve this target. We establish the proof that under certain assumptions the optimal solution of decentralized smart home scheduling is equivalent to that of the centralized method, reaching the theoretical lower bound of the community wide total electricity bill. In addition, an advanced cross entropy optimization technique is proposed to compute such a pricing scheme, which is also integrated with smart home scheduling. The simulation results demonstrate that our pricing scheme facilitates the significant reduction of both the community wide electricity bill and individual electricity bills compared to the state-of-the-art smart home scheduling technique. In particular, the community wide electricity bill can be reduced to only 0.06% above the theoretic lower bound.