Abstract

Existing work in energy demand side management focuses on the interaction between the utility grid and consumers. However, the previous technique is not focused on energy trading in local community of a renewable energy generation, distributed demand side management and not suitable for real-time environment. This paper presents a distributed demand side management system among multiple homes in community microgrid, with the integration of the internet of things smart meter and in the presence of renewable energy sources. The proposed energy consumption game is formulated for minimizing the cost of electricity in the individual home and the total cost of energy consumption in the whole community. The smart home users are playing game by optimizing their own daily energy consumption of appliances. The multiple participants include the self renewable generation of users, shared community microgrid and optional utility company. Each participant applies its best strategy to minimize energy consumption cost and users can maintain their own privacy of energy consumption. Moreover, the proposed scheme is distributed on blockchain, which provides a trusted communication medium between the participants. It enforces the autonomous monitoring of smart appliances and the billing of electricity consumption via smart contracts. Solidity smart contract is deployed to facilitate the execution of transactions without the involvement of third party in the smart community. Comparison of the results show that the proposed approach minimizes the total cost of energy consumption as well as each user's energy consumption cost.

Highlights

  • The energy demand is increased steadily over the coming years. This energy demand driven from humans, industries, agriculture and electric vehicles is expected the growth will be increased in the order of 40% by the year 2030

  • A day of 24 hours is divided in 96 time slots and one time slot interval is equal to power generation profile is plotted for single home which varies from 0 to 1.85kW

  • Energy consumption has increased in the time slot where electricity prices are low and renewable energy is available

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Summary

INTRODUCTION

The energy demand is increased steadily over the coming years. This energy demand driven from humans, industries, agriculture and electric vehicles is expected the growth will be increased in the order of 40% by the year 2030. A game theoretic mathematical model is proposed to schedule the appliances of an individual home in a smart community based on electricity price and to improve the participant’s privacy. Internet of thing smart meters (IoTs) are used as HECS to exchange the information between market participants i.e., consumers/prosumers, community microgrid and the utility grid. These IoT-SMs are used to control the information in bidirectional, control the home appliances and act as control centre in distributed market. Consumers share their energy consumption profile to the energy provider and maintained the privacy. All the information of user is private at HECS controller

ENERGY RESOURCES
CLASSIFICATION OF SMART APPLIANCES
PRICING
DISTRIBUTED ALGORITHMS
BLOCKCHAIN IMPLEMENTATION FOR ENERGY MANAGEMENT AND APPLIANCES SCHEDULING
RESULTS AND DISCUSSION
CONCLUSION AND FUTURE DIRECTIONS
Full Text
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