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Smart Grids and Energy Storage Systems

Smart Grids and Energy Storage Systems: Powering the Future of Energy In today’s rapidly evolving energy landscape, the push towards sustainability, efficiency, and reliability is stronger than ever. Traditional power grids, though robust in their time, are no longer sufficient to meet the demands of a modern, digital, and environmentally conscious society. This is where smart grids and energy storage systems (ESS) come into play — revolutionizing how electricity is generated, distributed, and consumed. What is a Smart Grid? A smart grid is an advanced electrical network that uses digital communication, automation, and real-time monitoring to optimize the production, delivery, and consumption of electricity. Unlike conventional grids, which operate in a one-way flow (from generation to end-user), smart grids enable a two-way flow of information and energy. Key Features of Smart Grids: Real-time monitoring of power usage and quality. Automated fault detection and rapid restoration. Int...

Omega, Theta notation

OMEGA NOTATION (Ω)
The Omega notation provides a tight lower bound for f(n). This means that the function can never do better than the specified value but it may do worse. 
Ω notation is simply written as, f(n) ∈ Ω(g(n)), where n is the problem size and 
Ω(g(n)) = {h(n): ∃ positive constants c > 0, n0  such that 0 ≤ cg(n) ≤ h(n), ∀ n ≥ n0}.
Hence, we can say that Ω(g(n)) comprises a set of all the functions h(n) that are greater than or equal to cg(n) for all values of n ≥ n0.
If cg(n) ≤ f(n), c > O, ∀ n ≥ nO, then f(n) ∈ Ω(g(n)) and g(n) is an asymptotically tight 
lower bound for f(n).
Examples of functions in Ω(n2) include: n2, n2.9, n3+ n2, n3
Examples of functions not in Ω(n3) include: n, n2.9, n2
To summarize, 
• Best case Ω describes a lower bound for all combinations of input. This implies that the function can never get any better than the specified value. For example, when sorting an array the best case is when the array is already correctly sorted.
• Worst case Ω describes a lower bound for worst case input combinations. It is possibly greater than best case. For example, when sorting an array the worst case is when the array is sorted 
in reverse order.
• If we simply write Ω, it means same as best case Ω.

THETA NOTATION (Θ)
Theta notation provides an asymptotically tight bound for f(n). Θ notation is simply written as, 
f(n) ∈ Θ(g(n)), where n is the problem size and Θ(g(n)) = {h(n): ∃ positive constants c1, c2, and n0
 such that 0 ≤ c1g(n) ≤ h(n) ≤ c2
g(n), ∀ n ≥ n0}. 
Hence, we can say that Θ(g(n)) comprises a set of all the functions h(n) that are between c1g(n)and c2g(n) for all values of n ≥ n0.
If f(n) is between c1g(n) and c2g(n), ∀ n ≥ n0,then f(n) ∈ Θ(g(n)) and g(n) is an asymptotically tight bound for f(n) and f(n) is amongst h(n) in the set.
To summarize, 
• The best case in Θ notation is not used.
• Worst case Θ describes asymptotic bounds for worst case combination of input values. 
• If we simply write Θ, it means same as worst case Θ.

OTHER USEFUL NOTATIONS
There are other notations like little o notation and little ω notation which have been discussed below.
Little o Notation
This notation provides a non asymptotically tight upper bound for f(n). To express a function using this notation, we write 
f(n) ∈ o(g(n)) where
o(g(n)) = {h(n) : ∃ positive constants c, n0
 such that for any c > 0, n0 > 0, and 0 ≤ h(n) ≤ cg(n), ∀ n ≥ n0}.
This is unlike the Big O notation where we say for some c > 0 (not any). For example, 5n3 = O(n3) is asymptotically tight upper bound but 5n2 = o(n3) is non-asymptotically tight bound for f(n).
Examples of functions in o(n3) include: n2.9, n3 / log n, 2n2
Examples of functions not in o(n3) include: 3n3, n3, n3 / 1000

Little Omega Notation (w)
This notation provides a non-asymptotically tight lower bound for f(n). It can be simply written as,f(n) ∈ ω(g(n)), whereω(g(n)) = {h(n) : ∃ positive constants c, n0 such that for any c > 0, n0 > 0, and 0 ≤ cg(n) < h(n),∀ n ≥ n0}.
This is unlike the Ω notation where we say for some c > 0 (not any). For example, 5n3 = Ω(n3) is asymptotically tight upper bound but 5n2 = ω(n3) is non-asymptotically tight bound for f(n).
Example of functions in ω(g(n)) include: n3 = ω(n2), n3.001 = ω(n3), n2
logn = ω(n2)
Example of a function not in ω(g(n)) is 5n2 ≠ ω(n2) (just as 5≠5)
An imprecise analogy between the asymptotic comparison of functions f(n) and g(n) and the relation between their values can be given as:
f(n) = Ω(g(n)) ≈ f(n) ≥ g(n) f(n) = ω(g(n)) ≈ f(n) > g(n)

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