<｜begin▁of▁sentence｜>### Instruction:
As a renewable energy engineer working on a project in a remote location, you've been tasked with designing and developing a renewable energy microgrid to power a small community. To model the interconnected nature of the microgrid, you'll need to create a growing random graph with 30 nodes to represent the various energy sources, storage units, and distribution points within the microgrid. Each new component you add to the graph should initiate two connections and point them to the most recently added component to simulate the interconnected nature of the microgrid. To accomplish this, you can leverage the Growing_Random function in igraph to generate and visualize the graph, providing an insightful representation of the interconnected energy system.
### Response:
import igraph as ig

# Parameters for the Growing Random Graph
g = ig.Graph.Growing_Random(n=30, m=2, directed=True, citation=True)

# Plot the graph (optional)
ig.plot(g, target='growing_random_graph.png')
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