Active-reactive Power Stability Analysis a Micro Grid in Grid to Connected Mode Based on Particle Swarm Optimization (PSO) Including Model Information

Aims: The aim of this paper is optimal active-reactive power flow between main grid and micro-grid consists of two parallel Distributed Generation (DG) units.

Study Design: Design of the study is applied with optimization algorithm for proposed controller power control policy. Power controller is designed to active-reactive power (P-Q) control policy.

Place and Duration of Study: IAU, Iran, February 2015-January 2016.

Methodology: This paper, with using of Particle Swarm Optimization (PSO) and model information analysis and control active and reactive power stability of a micro-grid includes two parallel DG units. Particle Swarm Optimization (PSO) model of proposed controller includes an inner current control loop and an outer power control loop based on synchronous reference frame and conventional PI regulators. PSO algorithm is used for real-time self-tuning power control parameters. Paper’s simulation is modeled in MATLAB/Simulink environment. As well as, PSO algorithm is programmed in M-file of MATLAB.

Results: Simulation result show satisfactory performance active and reactive power of system. As well as, in the paper, control objectives to identify generator angle reference signal and flux, and system dynamic performance improvement are used. As well as, the paper provided active-reactive power flow control between main grid and micro-grid includes DG units, and controller response in situations where load is higher or much lower than DG unit power rate. Paper’s proposed policy suggests that required load power equally between micro-grid and main grid based on PSO algorithm and using information model during load changing is shared, to fast dynamic response and stable operation is reached.

Conclusion: The paper is presented a power (P-Q) control policy for micro-grid based on PSO algorithm. This is done by proposed active and reactive power controller based on PSO algorithm for real-time self-tuning. In the paper, active and reactive power flow adjustment when that micro-grids interconnected are connected to the network has been proposed. Therefore, peak correction effectively reduces imported power from electric utility to half. In conclusion, this policy could be have significant implications for micro-grid scenario: reducing dependence on the main power system, increasing penetration in micro-source market, reduce electricity costs and improve sustainability.