Abstract

Participating in the ancillary services market, alongside the day-ahead market, can be

economically beneficial for market actors. However, adopting an optimal bidding strategy is not

straight forward. The decision-making process is subject to uncertainty, due to the prices being

unknown before gate closure times. Furthermore, at some instances, the day-ahead production

schedule might have to change to obtain the ability of reserving capacity.

Previous research have studied the gains of adopting a coordinated bidding strategy. However,

most of this research focus on the day-ahead market and the intraday market. Less focus it put

on the ancillary services market. Additionally, smaller case studies are often carried out in

previous research. For producers owning multiple power plants, treating every plant individually

turns into a time consuming and complex process.

This project constructs a model that instead uses a top-down approach. A system of

hydropower plants is aggregated into one curve, representing the water valuation. This,

together with a representation of available capacity for the system, gives the cost of delivering

capacity. The cost is incurred through not producing optimally on the day-ahead market.

Thereafter, modern portfolio theory is applied when determining how to allocate between the

different products. Modifications to the traditional theory are made in order to better suit this

context. Price forecasts are modelled as expected return, and historical price forecasting errors

represents the risk.

The model output is bid ladders for all capacity ancillary services. A top-down approach makes

it possible for large scale producers to adopt the methodology, and results in a structured way

of constructing the bids, while aiming at spreading the risk.