Evaluation of hydropower upgrade projects - a real options approach

When evaluating whether to refurbish existing hydropower plants or invest in a new power plant, there are two important aspects to take into consideration. These are the capacity chosen for the production facilities and the timing of the investment. This paper presents an investment decision support framework for hydropower producers with production facilities due for restoration. The producer can choose between refurbishing existing power plants and investing in a new production facility. A real options framework is proposed to support the investment decision. Using a case from Norsk Hydro ASA, a Norwegian hydropower producer, we employ the framework to evaluate the investment opportunities. Our main contribution is an approach that combines hydropower scheduling and real options valuation, and the results from our analysis suggest feasible investment strategies for Norsk Hydro ASA.Electricity price uncertainty; reservoir management; hydroelectric scheduling; investment under uncertainty; electricity markets

Profitability of a Hydro Power Producer Bidding in Multiple Markets - An Analysis of the Specific Case of Tokke-Vinje Hydro Power System

The main topic of this project has been to study the production scheduling of a hydro power producer exposed to the day-ahead, balancing and capacity market. The objective was to find what profit the producer may achieve by strategically bid in the above mentioned markets. A prototype model that undertakes this task has been developed by SINTEF Energy Research as a part of their project "Integrating Balancing Markets in Hydro Power Scheduling Methods". It is a multi-stage, multi-scenario, short-term deterministic model programmed in AMPL. To examine the potential profit a producer may gain by participating in the balancing market, the model has been run with and without the balancing market included in the simulation. The simulations have shown that a hydro power producer increases the expected income by participating in the balancing market. The model has been run with both Nordic and German day-ahead prices. The German day-ahead prices lead to even greater increase in profits when including the balancing market. The simulations have also benn done with higher price volatility, which resulted in a further increase in profits. Simulations have been done with different amounts of reserved capacity in the capacity market, with measures to reduce risk and with implementation to enforce acceptable reservoir behavior. The possibility of gathering profits from the capacity market proved to be limited. However, this conclusion is based on the prices that have been seen since the market was introduced in 2014 and may change if the prices rise

Detailed long-term hydro-thermal scheduling for expansion planning in the Nordic power system

acceptedVersio

A Planner-Trader Decomposition for Multi-Market Hydro Scheduling

Peak/off-peak spreads on European electricity forward and spot markets are eroding due to the ongoing nuclear phaseout and the steady growth in photovoltaic capacity. The reduced profitability of peak/off-peak arbitrage forces hydropower producers to recover part of their original profitability on the reserve markets. We propose a bi-layer stochastic programming framework for the optimal operation of a fleet of interconnected hydropower plants that sells energy on both the spot and the reserve markets. The outer layer (the planner's problem) optimizes end-of-day reservoir filling levels over one year, whereas the inner layer (the trader's problem) selects optimal hourly market bids within each day. Using an information restriction whereby the planner prescribes the end-of-day reservoir targets one day in advance, we prove that the trader's problem simplifies from an infinite-dimensional stochastic program with 25 stages to a finite two-stage stochastic program with only two scenarios. Substituting this reformulation back into the outer layer and approximating the reservoir targets by affine decision rules allows us to simplify the planner's problem from an infinite-dimensional stochastic program with 365 stages to a two-stage stochastic program that can conveniently be solved via the sample average approximation. Numerical experiments based on a cascade in the Salzburg region of Austria demonstrate the effectiveness of the suggested framework