Framework for Network-Constrained Cooperative Trading of Multi-Microgrid Systems

Abstract

The rising penetration of renewable energy sources (RESs) has led to increased research interest in the optimal scheduling and management of multi-microgrid (MMG) systems. This is due to the potential economic benefits which can be derived from the sharing of resources between the MGs which constitute the MMG. Advanced optimization procedures such as robust optimization (RO) frameworks have been proposed in the literature to handle any uncertainties caused by the stochastic nature of the RES generation, the load demand, and the electricity prices. However, the existing works in the literature do not consider the nonlinear network constraints of individual MGs which might significantly impact the power balance and the power sharing between MGs in MMG systems. This paper proposes a cooperative trading scheme including a two-stage network-constrained robust energy management system to optimize the resource utilization within each MG and the sharing of resources between the constituent MGs of a MMG system. The results clearly highlight the performance of the proposed approach and the impact of including the AC network constraints on the optimal dispatch of the MMG system under varying uncertainties.

Distributed control strategy for transactive energy prosumers in real‐time markets

“…In this subsection, we develop distributed algorithm for solving problem (22). Towards this end, this problem is first expressed in a uniform compact matrix form for mathematical conciseness, as shown below, min f…”

“…C i.t (22) st. ( 1)-( 10), ( 12)-( 16), (20) Notice that all constraints stated in ( 1)-( 10), ( 12)-( 16), ( 20) are compact and convex, whereas the objective function is also strictly convex. Hence, the problem is a convex optimization problem with unique optimal solution [27].…”

“…Because of complexity of network modelling, it is impractical to decouple this constraint directly, we firstly reformulate problem ( 23) by introducing auxiliary variables z i for each prosumer, which represent the duplicate of part variables in x i on the side of SO. Note that in problem (22), z i includes the net real power and net reactive power of prosumer i, therefore, detailed energy production and consumption information in prosumers are not shared, which ensures the privacy and autonomy of individual prosumers. The reformulated problem (30) is shown below,…”

“…We bring constraint (29) to make sure the reformulated problem ( 23) is equivalent to primary problem (22). Then we use a dual decomposition approach to decouple constraint (29).…”

“…Ref. [22] uses OPF to study the energy sharing among multi‐microgrids, but only considers nonlinear network constraints within individual microgrids. A decentralized control strategy is proposed in [23] for a network of microgrids by introducing power link agents, but line congestion and voltage violation are not considered.…”