Coordination of wind generation and demand response to minimise operation cost in day‐ahead electricity markets using bi‐level optimisation framework

The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand

“…A power system network represents an optimal power flow (OPF) model with a number of N b buses, and N l transmission lines are considered [25]. In the model, N is the set of busses and N the sets of the transmission lines, respectively.…”

“…The power flow in the lines connecting the bus i and j are represented by Equation 3. The details refer to [25,45,46]. The transmission line and generation supply limits are provided in Equations (4)-(6), respectively.…”

“…The lower-level problem fixes the optimal DR amount to be traded and the DR transaction cost. The DRX market can be constructed as a directed graph, L: = (N , A), indicated by the node set, N , composed with an arc set, A ⊂ (m, j), joining the trading node m and j as presented in [25]. Two different nodes in L, namely N : = {1, 2, .…”

“…Energies 2018, 11, 3296 6 of 22 set, N, composed with an arc set, A ⊂ (m, j), joining the trading node m and j as presented in [25]. Two different nodes in L, namely N a : = {1, 2, …, Na} and N r : = {1, 2, …, Nr}, corresponding for the DR aggregator and DR purchaser (as see Figure 2).…”

“…This paper proposes a DR integrated bi-level optimization framework. The bi-level optimization is a special kind of mathematical program, where an optimization problem contains another optimization problem as a constraint [24][25][26]. The outer and inner optimization tasks in the bi-level set are commonly referred to as the upper-level and lower-level optimization problems, respectively [27].…”