Power plant photovoltaic energy storage project bidding

What is the optimal bidding strategy for a virtual power plant?

This paper proposes an optimal bidding strategy model of a virtual power plant (VPP) in the day-ahead market (DAM) that contains energy, reserve, and regulation markets. The VPP aggregates the wind farm (WF), photovoltaic power (PV), energy storage (ES), gas turbine (GT), and hydropower station (HS).

Can virtual power plants participate in electricity market bidding?

If the capacity of the storage station is large enough to stabilize the fluctuation of the output of the wind and photovoltaic power, virtual power plants can participate in the electricity market bidding.

Why do wind power and PV units have high bidding output?

In contrast, wind power and PV units maintain high bidding output levels throughout the day, benefitting from their green and low-carbon characteristics that ensure competitiveness in the coexistence of green certificates and carbon trading.

How does a VPP bidding strategy affect internal diversified entities?

Furthermore, the study examines the VPP bidding strategy and the output characteristics of internally diversified entities. The integration of green certificates and carbon trading mechanisms enhances the economic income of VPP and contributes to an increase in the percentage of renewable energy output.

What is the penalty cost for forecast errors in photovoltaic power generation?

When the forecast errors of wind power and photovoltaic power generation are within this confidence interval, there will be no penalty cost. For the prediction errors outside the confidence interval, this study uses two-sided superquantiles to determine the expected value of the uncertain error, which in turn generates a corresponding penalty cost.