Climate change mitigation requires governmental intervention and there are various measures that can achieve this. While economists generally advocate first-best instruments, the reality is rather different, as subsidy schemes are commonly used for supporting renewable energy sources. The supporters of these schemes often argue that investment risk reduction is essential to achieving ambitious environmental targets. In this paper, we compare four different instruments (carbon cap, carbon tax, minimum renewable quota, and feed-in tariffs / renewable auctions) in terms of effectiveness, efficiency, and mitigation of investment risks. Risks are assessed assuming an uncertain investment environment, represented by different information shocks on demand, investment, and fuel cost. We employ an electricity market equilibrium model (generalized peak load pricing model) of the future German electricity market implemented as a linear optimization problem. Beginning from a long-run equilibrium, single input parameters such as demand, fuel prices, and investment costs are varied to simulate the arrival of new information. Rerunning the model with partially fixed capacities enables us to analyze the sequential adjustment of the power generation portfolio toward a new equilibrium over time. As expected, we find that quantity-based instruments are effective in ensuring the achievement of quantitative goals—notably a certain emission level. However, risks for investors are rather high in such cases. While our analyses confirm that the first-best instruments—carbon cap and carbon tax—provide the most efficient trade-off between emission reduction and cost, we also establish that investment risks are lower with price-based mechanisms. Particularly feed-in tariffs / renewable auctions provide the possibility of substantially limiting risks by diversification even when only electricity market assets are considered.@en

The value of day-ahead solar power forecasting improvements was analyzed by simulating the operation of the Independent System Operator - New England (ISO-NE) power system under a range of scenarios with varying solar power penetrations and solar power forecasting improvements. The results showed how the integration of solar power decreased operational electricity generation costs, by decreasing fuel and variable operation and maintenance costs, while decreasing start and shutdown costs of fossil fueled conventional generators. Solar power forecasting improvements changed the impacts that the uncertainty of solar power has on bulk power system operations; electricity generation from the fast start and lower efficiency power plants, ramping of all generators, start and shutdown costs, and solar power curtailment were all reduced. These impacts led to a reduction in overall operational electricity generation costs in the system that translates into an annual economic value for improving solar power forecasting.@en