Showing 3 results for Power Market
A. Rabiee, H. A. Shayanfar, N. Amjady,
Volume 5, Issue 3 (9-2009)
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.
N. Tabrizi, E. Babaei, M. Mehdinejad,
Volume 12, Issue 1 (3-2016)
Abstract
Reactive power plays an important role in supporting real power transmission, maintaining system voltages within proper limits and overall system reliability. In this paper, the production cost of reactive power, cost of the system transmission loss, investment cost of capacitor banks and absolute value of total voltage deviation (TVD) are included into the objective function of the power flow problem. Then, by using particle swarm optimization algorithm (PSO), the problem is solved. The proposed PSO algorithm is implemented on standard IEEE 14-bus and IEEE 57-bus test systems and with using fuzzy satisfying method the optimal solutions are determined. The fuzzy goals are quantified by defining their corresponding membership functions and the decision maker is then asked to specify the desirable membership values. The obtained results show that solving this problem by using the proposed method gives much better results than all the other algorithms.
F. Askari, A. Khoshkholgh,
Volume 17, Issue 2 (6-2021)
Abstract
The battery of electric vehicles (EV) can be charged from the power grid or discharged back to it. Parking lots can aggregate hundreds of EVs which makes them a significant and flexible load/generation component in the grid. In a smart grid environment, the smart parking lot (SPL) can benefit from the situation of the simultaneous connection to the EVs and power grid. This paper proposes a new algorithm to maximize SPL profit from participation in the forward and spot markets. Monte-Carlo simulation is used to determine the participation of the SPL in the forward market. Then an economic model is proposed to optimize the charging or discharging time table of EVs at any hours of a day and SPL participation in the spot market in a way that maximum SPL profit and satisfaction of EV owners can be gained. The Genetic Algorithm (GA) is used to solve this optimization problem.
