Nonlinear inverse demand curves in electricity market modeling

In large-scale energy market models, the price–demand relationship is usually represented by a linear function. this paper, nonlinear demand functions are fitted to electricity bid data; in particular, exponential and polynomial (cubic) estimated from EPEX day-ahead data (i.e. Central Western European area). The corresponding game-theoretic, models were successfully solved using Extended Mathematical Programming framework after suitable adaptation for conjectural variations. Additionally, sufficient conditions existence of equilibrium solutions tested. Numerical results show that curves lead an improved modeling especially high price (peak) load periods lower levels implied power, which can be considered more realistic markets have strong transparency measures.