Florentina Paraschiv

Medium-term planning for thermal electricity production

In the present paper, we present a mid-term planning model for thermal power generation which is based on multistage stochastic optimization and involves stochastic electricity spot prices, a mixture of fuels with stochastic prices, the effect of CO

Prediction of extreme price occurrences in the German day-ahead electricity market

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On the Construction of Hourly Price Forward Curves for Electricity Prices

2 emission prices and various types of further operating costs. Going from data to decisions, the first goal was to estimate simulation models for various commodity prices. We apply Geometric Brownian motions with jumps to model gas, coal, oil and emission allowance spot prices. Electricity spot prices are modeled by a regime switching approach which takes into account seasonal effects and spikes. Given the estimated models, we simulate scenario paths and then use a multiperiod generalization of the Wasserstein distance for constructing the stochastic trees used in the optimization model. Finally, we solve a 1-year planning problem for a fictitious configuration of thermal units, producing against the markets. We use the implemented model to demonstrate the effect of CO

Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation

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The impact of renewable energies on EEX day-ahead electricity prices

2 prices on cumulated emissions and to apply the indifference pricing principle to simple electricity delivery contracts.

Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks

With the liberalization of global power markets, modeling of exchange traded electricity contracts has attracted significantly the attention of both academic and industry. In this paper we offer an overview of the most common deseasonalization techniques and modeling approaches in the literature. We extract the deterministic component of EEX Phelix hourly electricity prices and we discuss different financial and time series models for their stochastic component. Additionally, we apply Extreme Value Theory (EVT) to investigate the tails of the price changes distribution. Generally our results suggest EVT to be of interest to both risk managers and portfolio managers in the highly volatile electricity markets.