Microgrid Capacity Design

What is microgrid capacity planning?

Microgrid is considered an efficient paradigm for managing the massive number of distributed renewable generation and storage facilities. The optimal microgrid capacity planning is a non-trivial task due to the impact of randomness and uncertainties of renewable generation sources, and the adopted energy management strategies.

Why is dcgan used in microgrid capacity planning?

The DCGAN is adopted for scenario generation to produce a sufficient number of power generation scenarios to cover the diverse system operational patterns. These scenarios are further clustered as a set of representative scenarios that are incorporated into the optimization process to obtain the robust microgrid capacity planning solution.

Is there a capacity planning solution for grid-connected microgrid based on scenario generation?

This paper presented an optimal capacity planning solution for grid-connected microgrid based on scenario generation considering multi-dimensional uncertainties. The efficient DCGAN based scenario generation method is developed to describe the uncertain behaviors of renewable power generation.

What is the optimal capacity configuration model for a grid-connected microgrid?

An optimal capacity configuration model of the grid-connected microgrid is proposed, which comprehensively considers economic cost, renewable energy utilization efficiency and carbon emissions. Through the combination with the previous work, it provides a new solution to the problem of microgrid planning.

What is Microgrid technology?

It is a small-scale power system with distributed energy resources. To realize the distributed generation potential, adopting a system where the associated loads and generation are considered as a subsystem or a microgrid is essential. In this article, a literature review is made on microgrid technology.

What is a microgrid design analysis?

For a design analysis, it is useful to conduct system modeling to match microgrid loads with generation on an hourly, 15-minute, or 1-minute basis. This type of modeling can provide a detailed look into how a microgrid can supply loads from different generation sources at each time step throughout the course of a year.