The origin of microgrid power flow calculation

How can a microgrid be optimally operated?

In island operation, the microgrid must regulate its voltage and frequency usually through droop control. Furthermore, the local energy resources have to be optimally operated to meet changing load demands at minimum cost. This optimization challenge requires efficient power flow analysis.

What is a microgrid (MG)?

1. Introduction A microgrid (MG) is a promising paradigm of electric power systems which integrates distributed generation (DG) units, energy storage systems and controllable loads to maintain the power supply in a defined area . The applications of power electronic devices in MGs have improved the flexibility of power system operation.

What is a power flow method?

It also means that it unable to obtain the consistent solutions for voltage magnitudes and phase angles of the whole nodes in a power system. The commonly used power flow calculation methods include Forward–backward Sweep Method , Direct Solution , Modified Newton Method and Zbus Gaussian Method .

What are the different types of power flow calculation methods?

The commonly used power flow calculation methods include Forward–backward Sweep Method , Direct Solution , Modified Newton Method and Zbus Gaussian Method . All these methods involve iterative computation, which is the most time consuming part of the power flow calculation.

What is probabilistic power flow?

Probabilistic power flow (PPF) is an effective method to evaluate the steady state of power systems with uncertainties [10]. The Monte Carlo simulation (MCS) [11], [12], [13], point estimate method (PEM) [14], [15], [16] and cumulant method (CM) [17], [18] are widely used in PPF calculation.

Can a nodal power imbalance model be used to calculate power flow?

Based on a nodal power imbalance model for power flow calculation, we used penalized least squares to fit the constraints and construct a complete model for power flow calculation. Then, we transformed the model into a nonlinear least squares problem by calculating the initial values as the initial conditions for the subsequent algorithms.