EPEC approach for finding optimal day-ahead bidding strategy equilibria of multi-microgrids in active distribution networks

Linearizing Bilinear Products of Shadow Prices and Dispatch Variables in Bilevel Problems for Optimal Power System Planning and Operations

“…Because we wish to linearize the bilinear product λ n,t y e,n,t in (28a), which is only defined for the PV nodes, we only need to check the linearization conditions for the components of the lower level model (29) that are relevant to the PV nodes. A Julia module to programatically check the linearization conditons, including for separable problems like this example, is available in [20] 4 .…”

“…Fernandez-Blanco et al 2016 [3] is the first to find a linearization for the same bilinear terms (products of lower level primal and dual variables) in the upper level of a bilevel program for revenue adequacy constraints. More recently, Naebi et al 2020 [4] forms a bilevel problem to optimize the bidding strategy of a microgrid owner in a day ahead market. The upper level minimizes operating costs from the microgrid owner's perspective with the product of its exported power and the dual variable of the lower level, linear power flow load balance in its objective.…”

A Stackelberg Game-Based Approach for Transactive Energy Management in Smart Distribution Networks

“…To solve the mentioned model, bi-level programming has been suggested, in which the upper level minimizes the risk of the Disco, whereas two separate lower levels clear the DA WEM and LEM. Finally, a multi-leader-one-follower bi-level model has been proposed in [19] to optimize the bidding strategy of multi-microgrid owners that are competing in a LEM. In this framework, multi-microgrids, as leaders, submit the prices of their bids/offers to the DSO in such a way to minimize operating costs.…”

“…an Independent AG [6]    [7]    [8]    [9]    [10]    [11]    [12]    [13]    [14]    [15]    [16]    [17]    [18]    [19]    [20]    [21]    This Paper     Designing a distinct LEM to create a novel platform for the TE exchange at the distribution level.  Presenting a Stackelberg game-based approach to model a TE environment in which the exchanged energy between autonomous financial entities and the DSO results in the equilibrium of the system.…”

Optimal hierarchical energy management scheme for networked microgrids considering uncertainties, demand response, and adjustable power

“…The coordinating operation of MGs is performed at the upper level of optimisation by centralised optimisation, while the local management of MGs is implemented at the lower‐level. The optimal day‐ahead bidding strategy for transactive energy among MGs and DNO is formulated as bi‐level optimisation [22]. Unlike [18, 19], the MG owner acts as the leader and tries to minimise the total daily cost of the MMG system, while the cost of DNO is minimised in the lower‐level of optimisation.…”