Power distribution network design considering dynamic and differential pricing, buy-back, and carbon trading

The increase in energy demand and the effect of traditional energy generation supported by the penetration of technological advancements in renewable energy generation calls for an integrated power distribution network design. In this study, a power distribution network design with the establishment of distributed renewable energy resources and involvement of prosumers in energy system to generate, buy, and supply carbon-free energy is considered. The dynamic prices that cope with the dynamic demand of both prosumers and customers over the energy planning time horizon and the buy-back price to be paid to the prosumers are also considered. A mathematical model for power distribution network design, including carbon trading and a buy-back policy, was developed. The objective is to determine the generation capacity of the distributed renewable energy resources to be installed at different potential sites, the differential prices offered to prosumers and consumers, and the buy-back price while maximizing the profit of a power plant. A scenario-based stochastic solution approach and fuzzifying fuzzy parameters are provided to address the above problem. The results show that the power plant earns the most profit at a relation factor of 0.8 between the differential prices by offering the highest buy-back price to incentivize the prosumers. With the increase in the relation factor, the net profit of the power company decreases, but the buy-back price increases, while the dynamic prices remain unpredictable. The average buy-back price offered to prosumers was 62.4% of the average selling price.

Automated summary

This study considers the establishment of a power distribution network design with distributed renewable energy resources and the involvement of prosumers in the energy system. By developing a mathematical model and solution approach, the study determines the generation capacity of distributed renewable energy resources, differential prices, and buy-back price while maximizing the profit of a power plant. The results show that offering a high buy-back price to incentivize prosumers can lead to the highest profit.