ترجمه مقاله نقش ضروری ارتباطات 6G با چشم انداز صنعت 4.0
- مبلغ: ۸۶,۰۰۰ تومان
ترجمه مقاله پایداری توسعه شهری، تعدیل ساختار صنعتی و کارایی کاربری زمین
- مبلغ: ۹۱,۰۰۰ تومان
Abstract
In this paper, real-time energy trading in smart grid is modeled as an optimization process under uncertainties of demand and price information — a problem perspective that is divergent from the ones in the existing literature. Energy trading in smart grid is affected by demand uncertainties — intermittent behavior of renewable energy sources, packet loss in the communication network, and fluctuation in customers’ demands. Energy trading is also affected by price uncertainty due to the demand uncertainties. In such uncertainty-prone scenario, we propose the algorithm named ENTRUST using the principles of robust game theory to maximize the payoff values for both sides — customers, and grid. We show the existence of robust-optimization equilibrium for establishing the convergence of the game. Simulation results show that the proposed scheme performs better than the existing ones considered as benchmarks in this study. Utilities for the customers are also maximized in order to promote cost-effective and reliable energy management in the smart grid.
6. Conclusion
In this paper, we proposed a scheme for energy management under different uncertainties concerning demand and price in a smart grid. The performance of the algorithms proposed in the existing literature on the issue of energy management, in general, suffers from uncertainty constraints. Therefore, we modeled the energy management scheme as a robust optimization approach using robust game theory to account for these uncertainty constraints. In the proposed model, the customers and the grid act as players of the game. The theoretical analysis of equilibrium of the game model is also presented. The simulation results showed that using the proposed approach, improved energy management over the existing ones, is achievable. The future extension of this work includes improvement in the expectation of the real-time demand from the customers in order to overcome the overestimation issue. We saw that the proposed scheme overestimates energy demand from customers in case of very low packet loss rate. Therefore, in future, we also plan to incorporate this issue in the smart grid systems. It also includes the establishment of a network architecture for smart grid to minimize packet loss in the communication network. This will enable us to achieve improved reliability and cost-effectiveness in energy management.