Abstract
As small-scale distributed energy is gradually expanding, commercialization of peer to peer(P2P) energy trading that freely exchanges energy among individuals in various countries is being commercialized, and the Microgrids (MGs) are considered to be an optimal platform for P2P energy trading. Although conducting electricity trade among individuals without going through power companies is still in its infancy, it is expected to expand gradually as the awareness of the shared economy grows and the MG spreads. Research on more efficient trading systems is needed while trading energy in MG. Therefore we propose a more efficient energy trading system that minimizes the loss in proportion to the distance of the power line when energy trading is performed in the MG. We have constructed a virtual MG environment and experimented with energy trading scenarios. As a result, when the algorithm is applied, loss in proportion to the distance is reduced by 2.495% and energy trading becomes more active. The amount of energy and the number of trades increased by 1.5 times during the energy trading process.
Highlights
Thermal power generation and nuclear power generation are a large part of energy generation
In this paper we proposed an algorithm for minimizing the loss in proportion to the distance of the power line and optimizing the system during the energy trading process
Because small units of energy are traded, even small losses can have a significant impact on efficiency
Summary
Thermal power generation and nuclear power generation are a large part of energy generation. In case of using solar panel and wind turbine, it is difficult to control the output because it is highly influenced by environmental factors, and the prediction of the power generation amount is uncertain and it is difficult to accurately generate the planned power generation amount at the required point. To overcome these drawbacks, P2P energy trading system is expected to contribute to expanding small scale distributed resources and creating new market. In this paper we proposed an algorithm for minimizing the loss in proportion to the distance of the power line and optimizing the system during the energy trading process.
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