**2. Application**

The Monte Carlo simulation is applied for determination of hydrogen energy potential where hydrogen can be used as a save energy without any pollution control like fossil fuels. The atomic construction of hydrogen consists of only one proton and one electron, which can be found in the universe easily. In the universe,

**101**

*Applying Monte Carlo Simulation in New Tech DOI: http://dx.doi.org/10.5772/intechopen.91264*

cell will produce electricity, never losing its charge.

other elements in our environment.

space shuttles.

is needed.

tainty of a certain system.

for modelling risk in a system.

renewable energy systems [5].

deterministic results.

by decision-makers.

time period.

using suitable numerical computations.

hydrogen does not occur naturally as a gas on Earth, as it is always combined with

On the Earth, hydrogen can be found in organic compounds as hydrocarbons which can be used as gasoline, natural gas, earth gas and methanol or propane and with a heat separation procedure, it can be converted into reforming procedure. With electrolysis, hydrogen is separated from water into its component of oxygen where we can use this process for electrical energy. In sea boundary layer, some algae and bacteria, using sunlight as their energy source, even give off hydrogen under certain conditions. Hydrogen fuel is used by NASA as a fuel for

In praxis, hydrogen and oxygen combine in a fuel cell to produce electricity, heat and water where they are often compared with batteries for converting the chemical reaction into usable electric power. As long as fuel (hydrogen) is supplied, the fuel

For buildings, and as an electrical power source for electric motors propelling

In scientific research, this simulation (Monte Carlo) is a new technique in science which forms random variables as input results for risk assessment or uncer-

In new application on the basis of probability distributions such as normal, log normal, etc., the random variables or inputs are modelled, where different iterations or simulations are run for generating paths, and the outcome is arrived at by

In the application of Monte Carlo simulation for an exact solution, the hydrogen energy potential problem is solved by Monte Carlo simulation, which is used in a dynamic complex system that needs to be analysed, which is a probabilistic method

The Monte Carlo method is used also in physical science, statistics, artificial intelligence and robotics. In the example of the determination of hydrogen energy potential, the Monte Carlo simulation gives as a result a probabilistic estimate of uncertainty. But it is a useful tool for approximation of realty which gives never

The Monte Carlo simulation technique was observed in innovation extensively for modelling uncertain situations like hydrogen energy potential determination in

It is difficult to predict the real situation with absolute precision and accuracy, which can be attributed to the different parameters that can impact the outcome of a course of action. The Monte Carlo simulation can give all possible results for a new decision. It can thereby help us take improvements of a solution for a difficult situation under uncertainty. The probabilities of outcomes can be easily discussed

For instance, the Monte Carlo simulation can be used to compute the value

at risk of a portfolio where this method tries to predict the worst return expected from a portfolio, given a certain confidence interval for a specified

Hydrogen is a best energy carrier that is used by consumers in different ways. Other innovative energy sources, like the Sun and bioenergy, cannot produce energy all the time in the future where they could, for example, produce electric energy and hydrogen, which can be stored until it is needed. In the hydrogen generation, it can also be transported (like electricity) to locations where it

vehicles, fuel cells are new innovation for converting heat and electricity.

#### *Applying Monte Carlo Simulation in New Tech DOI: http://dx.doi.org/10.5772/intechopen.91264*

*Public Sector Crisis Management*

simulation process:

*Monte Carlo simulation [4].*

**Figure 1.**

computer chart is given as an example where the three steps are required in the

The discussion about the choosing of independent random variables will be given. But, the Monte Carlo simulation is applicable for dependent variables where

2.Generating many sets of possible inputs that follow the above properties.

The Monte Carlo simulation is applied for determination of hydrogen energy potential where hydrogen can be used as a save energy without any pollution control like fossil fuels. The atomic construction of hydrogen consists of only one proton and one electron, which can be found in the universe easily. In the universe,

Step 1: Sampling on random input variables X.

Step 3: Performing statistical analysis on the model output.

Monte Carlo methods generally follow the following steps:

1.Determining the statistical properties of possible inputs.

3.Performing a deterministic calculation with these sets.

The error on the results typically decreases as 1/√N [3].

Step 2: Evaluating model output Y.

it is needed to follow the three steps [2].

4.Analysing statistically the results.

**100**

**2. Application**

hydrogen does not occur naturally as a gas on Earth, as it is always combined with other elements in our environment.

On the Earth, hydrogen can be found in organic compounds as hydrocarbons which can be used as gasoline, natural gas, earth gas and methanol or propane and with a heat separation procedure, it can be converted into reforming procedure. With electrolysis, hydrogen is separated from water into its component of oxygen where we can use this process for electrical energy. In sea boundary layer, some algae and bacteria, using sunlight as their energy source, even give off hydrogen under certain conditions. Hydrogen fuel is used by NASA as a fuel for space shuttles.

In praxis, hydrogen and oxygen combine in a fuel cell to produce electricity, heat and water where they are often compared with batteries for converting the chemical reaction into usable electric power. As long as fuel (hydrogen) is supplied, the fuel cell will produce electricity, never losing its charge.

For buildings, and as an electrical power source for electric motors propelling vehicles, fuel cells are new innovation for converting heat and electricity.

Hydrogen is a best energy carrier that is used by consumers in different ways. Other innovative energy sources, like the Sun and bioenergy, cannot produce energy all the time in the future where they could, for example, produce electric energy and hydrogen, which can be stored until it is needed. In the hydrogen generation, it can also be transported (like electricity) to locations where it is needed.

In scientific research, this simulation (Monte Carlo) is a new technique in science which forms random variables as input results for risk assessment or uncertainty of a certain system.

In new application on the basis of probability distributions such as normal, log normal, etc., the random variables or inputs are modelled, where different iterations or simulations are run for generating paths, and the outcome is arrived at by using suitable numerical computations.

In the application of Monte Carlo simulation for an exact solution, the hydrogen energy potential problem is solved by Monte Carlo simulation, which is used in a dynamic complex system that needs to be analysed, which is a probabilistic method for modelling risk in a system.

The Monte Carlo method is used also in physical science, statistics, artificial intelligence and robotics. In the example of the determination of hydrogen energy potential, the Monte Carlo simulation gives as a result a probabilistic estimate of uncertainty. But it is a useful tool for approximation of realty which gives never deterministic results.

The Monte Carlo simulation technique was observed in innovation extensively for modelling uncertain situations like hydrogen energy potential determination in renewable energy systems [5].

It is difficult to predict the real situation with absolute precision and accuracy, which can be attributed to the different parameters that can impact the outcome of a course of action. The Monte Carlo simulation can give all possible results for a new decision. It can thereby help us take improvements of a solution for a difficult situation under uncertainty. The probabilities of outcomes can be easily discussed by decision-makers.

For instance, the Monte Carlo simulation can be used to compute the value at risk of a portfolio where this method tries to predict the worst return expected from a portfolio, given a certain confidence interval for a specified time period.
