Linking electricity prices and costs in bottom-up top-down coupling under changing market environments

For some time, regulatory reforms in Europe have aimed at electricity market liberalisation. One of the many consequences is that increasingly spot market transactions replace long- term contracts, thus redefining the way wholesale electricity prices are formed. With the increased impact of the spot market, short-term marginal cost becomes an important determinant of electricity pricing. At the same time, price regulation, while still present, has a declining influence on total revenues. Hence, large electricity producers are much less able to rely on long-term contracts that safeguard revenues covering average system cost plus a certain margin. Current low prices pose the question of how capacity additions will be paid for. Will policies eventually take liberalisation to a point of effective capacity competition where scarce capacities lead to a capacity rent being paid at the margin? In the resulting fully competitive equilibrium, market prices would be determined by long-term marginal cost. However, under the influence of concerns about supply security, any other mix of industri- al policy incentives is also conceivable. These considerations need to be taken into account when coupling bottom-up to top- down models to analyse energy policies and electricity markets including capacity addi- tions, international trade, and demand reactions. Choices have to be made regarding the way in which the costs of production generated by the Energy Systems Model are to be linked to the wholesale price of electricity in the Computable General Equilibrium (CGE) model. These choices reflect the modellers’ interpretation of pricing in changing electricty market environments: Pricing may have been dominated by average cost based regulation in past calibration periods, but could (gradually) shift to more competitive mechanisms over the simulation horizon. The particular choice of coupling variables for each model period is likely to have repercussions on the simulation results. With this in mind, we build a coupled bottom-up top-down framework that consists of two models: the technology-rich bottom-up model Cross Border TIMES Electricity Model (CROSSTEM), which represents 288 time-slices and endogenous electricity trade between Switzerland and its neighbouring countries, and the dynamic multi-sectoral Computable General Equilibrium (CGE) model GENESwIS of the Swiss economy. These two models are coupled through a soft link where the electricity generation production function in the CGE model is determined by the cost structure optimized by the bottom-up model and where the sectoral electricity demand variations that occur in the CGE as a result of changes in prices are sent back to the bottom-up model.