Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Abstract

With the promotion of the national "double carbon" goal, the power system is developing towards the direction of low-carbon transformation. In order to achieve the goal of "striving to peak carbon dioxide emissions by 2030 and striving to achieve carbon neutrality by 2060", we must actively promote the consumption of a high proportion of renewable energy from the grid, which is the most urgent issue to be addressed. In this chapter, access to clean energy will involve multiple aspects such as source, network, load and storage. However, due to the intermittent, random and volatile nature of wind power and photovoltaic power generation, the challenges faced by significant users of the power system are enormous. Traditional energy Internet dispatching adopts centralized dispatching. In this paper, by deploying edge nodes, the autonomous decision-making and autonomous collaboration of power grid nodes at all levels are enhanced, and the collaborative integration level of source, network, load and storage of smart power grid is improved. Aimed at the current power supply and demand imbalance, new energy access problems and energy storage problems. In this paper, a service adaptation algorithm based on dynamic priority is proposed based on the scenario of load storage integration of source network under renewable energy access. Experimental results show that, compared with other algorithms, this algorithm has lower scheduling time and execution time and better performance under the condition of ensuring the highest clean energy consumption rate and first-order load priority response.