Reduced Order Modeling of a Shipboard Power System

Reduced-order average-value models form the basis of a computationally efficient approach for studying shipboard power systems. As a result of neglecting fast states, this approach generally involves solving a set of differential algebraic equations. Although the reduced-order average-value modeling approach has been well studied in the literature, as simulation languages evolve the most programmatic approach to addressing the non-linear algebraic portion of the model changes as well. In this work, a number of approaches for implementing reduced-order average-value models of a small power system are compared.Center for Electromechanic

Application of a New Hybrid Method for Day-Ahead Energy Price Forecasting in Iranian Electricity Market

Abstract- In a typical competitive electricity market, a large number of short-term and long-term contracts are set on basis of energy price by an Independent System Operator (ISO). Under such circumstances, accurate electricity price forecasting can play a significant role in improving the more reasonable bidding strategies adopted by the electricity market participants. So, they cannot only raise their profit but also manage the relevant market more efficiently. This conspicuous reason has motivated the researchers to develop the most accurate, though sophisticated, forecasting models to predict the short-term electricity price as precisely as possible. In this article, a new method is suggested to forecast the next day's electricity price of Iranian Electricity Market. The authors have used this hybrid model successfully in their previous publications to predict the electric load data of Ontario Electricity Market [1] and of the Spinning Reserve data of Khorasan Electricity Network [2] respectively