Annular Directed Distributed Algorithm for Energy Internet

Abstract

This article investigates an annular directed distributed double optimal algorithm to manage many we-energy frameworks in energy management of energy Internet (EI). The we-energy (WE) is an integrated energy hub containing varied energy devices of different functions including multi-energy production, consumption, and conversion. On this basis, all WE models cooperate to search for a minimum value of an objective function. Energy management in EI has two main goals. On the one hand, it needs to attain the optimality of economy with influence about the fluctuation of distributed renewable energy and randomness of terminal users. On the other hand, the EI should protect the privacy of terminal users well. Besides, discovering optimality value in the oscillation near convergence point, EI also needs a decrease in communication frequency and refraining of Zeno behavior. Zeno behavior means some operation is triggered infinite times in finite times of iteration. For realizing these proposes, this literature establishes an EI system that transfers cyber information in an annular directed path. The algorithm in this EI system adopts a novel annular distributed double-control price guiding strategy. In addition, this algorithm employs other two methods including the alternating direction method of multipliers method and the Newton-downhill method to optimize economy and reach convergence, respectively. Meanwhile, that algorithm adopts a small positive constant $w$ to avoid Zeno behavior. The performance of that algorithm is demonstrated through simulation results. Moreover, the optimality, convergence analysis, and avoiding Zeno behaviors are strictly proved by convex optimization and the monotone-bounded convergence theorem.