Introduction
An important challenge of renewable generation is how to manage its weather dependence. For scenarios of high penetration of renewables, there is a risk of not supplying power during days of low wind or solar availability. A possible solution is a hybrid power plant which is able to provide baseload power regardless of the weather conditions. Such a power plant requires a large capacity energy storage system to shift the electricity production from periods of high availability of wind and solar to low availability. This requirement can be met by short-term (e.g. a Battery Energy Storage System) or long-term storage (e.g. hydrogen storage combined with electrolyzers and fuel cells). These two types of storage differ in many aspects, but most importantly in their price per unit of energy storage. The cost of short-term storage tends to be driven by its energy capacity. By contrast, long-term storage tends to have a low marginal cost for energy storage, but a high cost for power capacity.

In this context, this work addresses the following research questions:

• What is the optimal balance between short-term and long-term storage to satisfy baseload power production at minimal cost?
• What is the sensitivity of the sizing and total cost to storage cost assumptions and site characteristics?

Methodology
The design problem is modelled as a linear optimization problem for sizing and operation of the storage system of a hybrid power plant with the objective of maximizing profitability. We consider short and long-term storage with different cost assumptions. The power plant gets revenue from operating in the day-ahead market. The optimization is run for a one-year period, assuming perfect information about price and weather. Our study focuses on hybrid wind-storage power plants.

Main results and conclusions

We conduct an analysis for different offshore site locations in Northern Europe and different storage cost assumptions. As a result, the following conclusions are drawn:

• At expected future costs of long-term and short-term storage, the total power capacity of the storage system is approximately equal to the baseload power level.
• The higher the baseload level, the higher the share of long-term storage in the total energy and power capacity.
• At expected future storage costs, the cost of satisfying a baseload constraint is primarily driven by the cost of long-term storage.
• The main drivers for the cost of satisfying the baseload constraint are the baseload level and the share of renewable energy produced at a power above baseload.