[GRU, Mo 14:00] Grid and Renewables under Uncertainty

1.Transmission Investment under Uncertainty: The Case of Germany‐Norway (Fleten, Heggedal, Siddiqui)

Price differences between neighbouring regions and countries motivate the construction of large transmission lines. Analysis of such investment are complicated by the fact that we have uncertainty in prices and exchange rates, and also by the fact that the price differences between the regions is affected by the transmission line itself when it has been put into operation. We perform an analysis of a merchant investor holding an exclusive license to build transmission capacity between Norway and Germany. The method we employ is real options analysis. In order to estimate the parameters needed in the real options analysis, we construct a net present value model using a nonparametric approach for estimating the electricity price difference between the countries. We also include exchange rate uncertainty. For the real option analysis, we study two alternative projects; (1) building a 700 MW cable with a compound option to expand to 1400 MW, and (2) building a 1400 MW cable. The first alternative can be viewed as an option to build a 700 MW cable with the option to switch to a 1400 MW cable, under the restriction that some costs must be undertaken. We use the framework of Dècamps, Mariotti and Villeneuve (Irreversible investment in alternative projects) to study the real options value of the investment alternatives.

The construction of transmission capacity is regulated by the government in Norway and Germany. When granted a license to build transmission capacity, the companies are given a limited amount of time to decide whether to build the transmission line or not. By estimating the real optionsvalue and the net present value, we find the loss to society when forcing through an investment before the optimal time for construction is reached.

The result of our analysis is an improved basis for decision making from a company’s point of view. We also contribute to an expanded understanding and valuation of the effect of giving time limitations of licenses in energy investments, and the welfare losses this yields.

2.Modelling Financially Optimal Decisions of Network Operators under Regulatory Uncertainty (John)

The present change in the electricity generation pattern requires grid operators to adapt their networks. Electricity grids need to accommodate the connection and operation of new renewable energy generation sites. Conventional power plants reaching the end of their lifetimes will be replaced by new units with different technical properties and at different locations. Grid operators need to realize investment projects into their grid infrastructure in order to meet this continuously changing demand.

Modelling the impact of regulation
Besides technical and environmental requirements the essential precondition for carrying out such investments is the ability of grid operators to obtain the necessary financial resources. This ability, in turn, depends on the investment remuneration scheme which is foreseen in the relevant regulatory framework. Modelling the financial impact of the regulatory system is therefore a decisive strategic task for both regulatory institutions and regulated entities. The presented model captures key parameters of theoretically discussed and practically implemented regulatory frameworks. Model results are key financial figures which enable regulated entities to take financially rationale decisions.

Optimized decisions
This optimal decision taking process is modelled in a second step. Assuming financially rational behaviour the objective function of a grid operator is to maximize the present value of its asset investments. This optimization is constrained by budgetary limitations and technical properties of the envisaged investment projects.

Taking decisions under regulatory uncertainty
Practical experience evidences that essential parameters within regulatory systems are continuously revised and modified. Other relevant external parameters are also subject to ongoing changes. This leads to a risk exposure of regulated entities. The properties of this dynamic and uncertain environment are represented in the model by employing Monte Carlo simulations.

Main conclusions
It can be shown that different regulatory regimes and parameters heterogeneously impact the behaviour of financially rational, regulated companies. The existence of regulatory risk is a further source of influence on their decisions. The presented model derives financially optimal decisions based on objective criteria. In this sense, it can be used to support regulators and regulated companies both when taking individual decisions or in common initiatives to design appropriate regulatory systems.

3.Impacts of Load Flow Based Market Coupling in Europe – Analysis with a Zonal Electricity Market Model (Barth)