Demand response for frequency control of multi-area power system

Abstract

Over the last few years, lots of attentions have been given to the demand response (DR) for the frequency control. DR can be incorporated with traditional frequency control method and enhance the stability of the system. In this paper, the frequency control strategy of DR for a multiarea power system is specially designed. In order to quickly stabilize the frequency of different areas, the tie-line power is adopted as the additional input signal of DR. To get the optimal parameters of the control system, the frequency control problem is formulated as a multi-objective optimization problem, and the parameters such as the integral gains of secondary frequency control, the frequency bias parameters, and coefficients of DR are optimized. Numerical results verify the effectiveness of the proposed method.

Incremental Cost Consensus Algorithm for On/Off Loads to Enhance the Frequency Response of the Power System

“…It improves the inter-area oscillation damping and enhances the dynamic performance of the power system. Reference [14] develops a frequency control strategy of DR for an interconnected multiarea power system. The frequency deviation and the tie-line power are both adopted as the input signal of DR, and the optimal performance of the system is achieved by the genetic algorithm.…”

Long-Term Frequency Stability Assessment Based on Extended Frequency Response Model

“…The input of this module is the fuel flow. Therefore, the fuel flow is calculated based on feedwater flow with equation (7). The feedwater flow is the intermediate constraint variable in the extended frequency response model.…”

“…It even leads to blackouts, such as the cases in South Australia [4] and London [5]. Power system frequency security and stability controls are facing new challenges [6]- [7]. Therefore, it is necessary to study power system frequency dynamic behavior and stability within an extensive frequency deviation range.…”

Multi-objective optimization for electric water heater using mixed integer linear programming

“…The most common methods are the weighted summation method and the e-constraint method [22]. The weighted summation method can obtain the solution in different situations by changing weighting factors, which is also the most simple and effective method for solving multi-objective optimization problems [23,24]. Then we adopt the weighted summation method to combine the objective functions of multi-objective optimization problem to construct a single objective function.…”