Research on the Bi-Level Optimization Model of Distribution Network Based on Distributed Cooperative Control

Abstract

The uncertainty of high-permeability renewable energy output brings about great challenges to the operation control in distribution network. The traditional control mode has lower reliability, higher calculation and greater communication pressure. It is more difficult to realize the technical requirements of ''plug and play'' of power components. Therefore, a bi-level coordinated control model is proposed for the operation and energy management optimization of active distribution network with multi-microgrid in this paper. The consensus algorithm which exists in the multi-agent system is applied in the upper-level model and the capacity utilization ratio of the different microgrids is set as the consistent variable because the ratio of resistance and reactance is usually larger in distribution network and the interests in the different microgrid entities should be distributed fairly. Moreover, in the lower-level model, the lowest operating cost is the final goal and the model predictive control rolling optimization is utilized to reasonably allocate the output of the equipments in the microgrid according to the changing trend of renewable energy. Thereby the tracking of the upper-level control commands is realized. Finally, the simulations are conducted in the IEEE-33 nodes distribution system connected to a multi-microgrid to verify the feasibility and effectiveness of the proposed method, in which a reference for the optimal operation of higher penetration renewable energy to distribution network is provided.INDEX TERMS Bi-level model, consensus algorithm, distributed control, high-permeability, model predictive control. II. CONTROL STRATEGY OF MULTI-MICROGRID SYSTEM A. DISTRIBUTED COLLABORATIVE CONTROL

State-of-the-art review on energy sharing and trading of resilient multi microgrids

“…ADMM, a distributed method, was used to evaluate how changing carbon pricing may affect the system’s operation. In addition to operational constraints, non-linear power flow constraints are considered in Xu et al, 94 and a consensus algorithm is utilized to build the ideal scheduling model of each microgrid’s controllable distributed generations, resulting in the microgrid functioning stably in the optimal state. Although the consensus algorithm is applied extensively in MG optimization, other techniques are available in the literature, such as the distributed diffusion strategy, 95 which could converge to an optimality at a faster rate.…”

A scheduling framework for a multi‐agent active distribution network in presence of renewable energy sources

“…Accordingly, the local scheduling model of agent a should be changed to Equation (26). minimize C a to + 𝛿 a r subject to (1)- (20), and ( 27)-(30) (26) here, 𝛿 a r is the penalty term of the ADMM algorithm in the local model of agent a in iteration r, which should be updated iteratively according to Equations ( 27)- (29).…”

Investigating Impacts of CVR and Demand Response Operations on a Bi-Level Market-Clearing With a Dynamic Nodal Pricing

“…A competitive electricity market for a multimicrogrid based distribution system and investigates the interactions of DSO and microgrids in the proposed models in [16]. A bi-level coordinated control model for optimizing an active distribution network with several microgrids is presented in [17]. It is concluded in [18] that by using bilevel programming in a trans-active framework, microgrids can decrease their costs by trading energy with DSO.…”