Showing 2 results for Amjady
A. Rabiee, H. A. Shayanfar, N. Amjady,
Volume 5, Issue 3 (September 2009)
Abstract
This paper presents a new framework for the day-ahead reactive power market based on the uniform auction price. Voltage stability and security have been considered in the proposed framework. Total Payment Function (TPF) is suggested as the objective function of the Optimal Power Flow (OPF) used to clear the reactive power market. Overload, voltage drop and voltage stability margin (VSM) are included in the constraints of the OPF. Another advantage of the proposed method is the exclusion of Lost Opportunity Cost (LOC) concerns from the reactive power market. The effectiveness of the proposed reactive power market is studied based on the CIGRÉ-32 bus test system.
M. Esmaili, H. A Shayanfar, N. Amjady,
Volume 6, Issue 1 (March 2010)
Abstract
Congestion management in electricity markets is traditionally done using deterministic values of power system parameters considering a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties. The uncertainty sources that are modeled in the proposed stochastic framework consist of contingencies of generating units and branches as well as load forecast errors. The Forced Outage Rate of equipment and the normal distribution function to model load forecast errors are employed in the stochastic programming. Using the roulette wheel mechanism and Monte-Carlo analysis, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. Scenario reduction is adopted as a tradeoff between computation time and solution accuracy. After scenario reduction, stochastic congestion management solution is extracted by aggregation of solutions obtained from feasible scenarios. Congestion management using the proposed stochastic framework provides a more realistic solution compared with the deterministic solution by a reasonable uncertainty cost. Results of testing the proposed stochastic congestion management on the 24-bus reliability test system indicate the efficiency of the proposed framework.
