Microgrid Uncertainty Modeling Method

How uncertainty models affect microgrid planning?

Microgrid planning is highly affected by different uncertainty modeling methods. The planning results besides the benchmarks show economic and reliability improvement. The accuracy of models to capture the uncertainty of renewables significantly affects the planning and operation of renewable energy-based stand-alone (REB-SA) microgrids.

Is there a model for power outage uncertainty in a microgrid?

To counter this, an LAES model without isolated design was developed and integrated into the microgrid complex integer linear programming design framework. In Ref. , the information gap decision theory (IGDT) method has been utilized to model power outage uncertainty in the system's optimal performance.

What is a critical source of uncertainty in microgrids planning?

Load consumption is another critical source of uncertainty. The adequacy of reserves maintains the energy and power balance in the long-term planning and the reliable real-time operation of microgrids. Additionally, the capital and operation costs are essential issues in microgrids planning , , .

How does uncertainty affect a distribution microgrid?

The uncertainty in the output power of renewable resources, such as wind and photovoltaic (PV) energy, in distribution microgrids is a primary challenge for the operator as it impacts the network's capacity to host these sources. Uncertainty in the output power of renewable resources is one of the primary challenges the operator encounters in managing these sources in distribution microgrids.

What is a new data classification method in microgrid planning problem?

Introducing a novel data classification method in the microgrid planning problem for considering time-dependency in generated values, and the cross-dependency among different uncertainty sources. The rest of the paper is organized as follows. The mathematical models of renewable energy and microgrid components are presented in Section 2.

Why does microgrid planning have undersized components?

The time-dependent uncertainty of variables is also one of the most critical issues that should be considered. As a result of this, the planning process ends up with undersized components from the energy capacity viewpoint. Table 4. The results of microgrid planning with three simulation models (LPSP = 6.45e−4).