Energy storage bidding multi-branch input

How do generating units bid in dam & RTM?

The generating units submit energy bids in DAM and RTM based on their power-cost functions. The original model was quadratic which was linearised with five steps. The piece-wise linear power-cost function was used as their bid in DAM and RTM. For wind generators, it is assumed that their bidding price is 0, i.e. they sell with any market price.

How is the bidding strategy implemented?

The bidding strategy is implemented on the real-time price signals of Fig. 4 (the average of ten MCS) and is tabulated in Table 2. In this table, the two-level bids (one for energy and one for FRP) when the FRU or FRD prices are greater than 0.5$/MWh are demonstrated.

What is the bidding strategy of ESS based on energy and FRP price signals?

The bidding strategy of ESS based on energy and FRP price signals in order to maximise its profitability is described in Section 4. The case study and numerical results are investigated in Section 5 and eventually, the concluding remarks are presented in Section 6.

What is the optimal bidding strategy for ESSs in the FRP market?

This study introduces a stochastic optimisation framework for participation of ESSs in the FRP market. The proposed model formulates the optimal bidding strategy of ESSs considering the real-time energy, flexible ramp-up and ramp-down marginal price signals and the associated uncertainties.

When should a bid be greater than the energy capacity?

According to Fig. 3, the bid should be greater than with the energy capacity equal to in order to approach an optimal energy purchase. The FRU will be enabled if the ESS submits a bid with power level equal to the desired FRU value and a price between and .

What is the proposed bidding mechanism for energy trades and FRP?

The proposed mechanism is a two-level bidding action that the ESS should submit: one for energy trades and the other for FRP. The proposed solution is simulated on the IEEE 118-bus test system and MCS is performed to attain the expected real-time realised position.