Technical Analysis
The three sites chosen are representations of small, medium, and large sites. These sites were chosen as they will help us understand how the developed tool will be able to address our aim to achieve decarbonization for each site.
Weibull Distribution
The chance of wind speeds occurring at various velocities is described by the Weibull distribution in the context of wind speeds. The probability of detecting a specific wind speed at a specific location or over a specified time is depicted by the distribution curve. We can fit the Weibull distribution to the observed wind speeds and perform probabilistic calculations, such as calculating extreme wind speeds for return periods, estimating average wind speeds, and estimating the shape and scale parameters from the wind speed data.
Example of Weibull distribution
Insight
From the above distribution, it is clear that the average maximum wind speed is observed at a wind speed of 10- 12 m/s. This shows that the given site will have a wind speed in the said range, this will help the wind farm developers to design the components such as wind turbine generators, gearboxes etc that suites the wind speed. This will ensure a smooth operation and increased reliability on the model.
Energy Production Profile
The hourly energy production profile in a wind farm is a time-series data that displays the quantity of power produced by the wind turbines in the wind farm for each hour of the day. It is a crucial indicator of the wind farm's performance and may be applied for a number of things, including maximising operation and maintenance, forecasting output, and determining the wind farm's economic feasibility. The wind's strength and direction, the turbines' capacity, and efficiency, as well as the wind farm's architecture and design, all have an impact on the hourly energy output profile. The energy production profile will typically indicate more energy output during periods of strong, constant wind and lower output during periods of calm, variable wind.
Example of hourly production profile
Graphical User Interface (GUI) Of Tool
The graphical user interface is critical for the enhanced usability of the tool. This should include a clutter-free landing page which comprises of well-aligned data points. Another factor that will have a significant impact the usability is that the input-data points have to be easily available. This is done to ensure that anyone with a fundamental knowledge about wind power generation can use the tool.
As stated above the key inputs for the tools are straightforward data points that do not require significant probing. In fact, most of the above points are readily available in open sources, thus ensuring an extensive usability of the tool.
Annual Energy requirement trends
To understand the amount of energy that is generated from a site and the total energy that will be required for achieving decarbonization the following trends were observed with multiple runs.
Kentish Flats
Thannet
Hornsea 2
*Please note that the above-mentioned trial represents the value attained on each run of the MATLAB tool
To download MATLAB files click here.
Annual Energy Production and Energy required to produce Hydrogen
Annual energy production is calculated as the total energy that can be produced on site. This is a function of the total number of turbines, the sweep area, and the power factor of the turbine. Factors such as cut-in and cut-out speeds determine the times around which energy will not be generated from the turbine. As depicted in the graph, HS2 is the largest site with the largest number of turbines and the largest rotor diameter. This results in HS2 showing the largest output. Thanet and Kentish flats are relatively smaller sites and thus produce an equivalent amount of energy.
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The plot also covers the proportion of energy that is required to produce hydrogen from the annual energy production. It is observed that a larger site will have a higher proportion of energy that can be spared for hydrogen production, while a small site will have to spend almost all the energy produced on hydrogen generation.
Annual CO2 emissions saved per site
The net CO2 saved from the site represents the amount of CO2 that is potentially realized if the O&M activity was conducted using marine diesel oil pr marine fuel oil. The fuel requirement increase s with an increase in the number of sites as the distance traversed increases for a larger site. It is observed that a minimum of 32 MT of CO2 has been saved from O&M in HS2 whereas 4.04 MT of CO2 has been saved from O&M activities of Kentish flats.
Hydrogen Production and Annual Operational Trend Comparisons
The above plots relate the amount of hydrogen produced to the number of trips covered for O&M in a site and the total distance traversed for O&M activity in a site. It is evident that a larger site will have Larger probability of failure of turbines. The failures will warrant the movement of the vessel to rectify the fault. The size of the site will have a direct impact on the distance the vessel has to transverse (i.e., HS2 is 89 km away from shore and Kentish Flats are just 8.6 km away from shore) and the number of trips it has to take. The larger number of trips and their associated fuel requirements will result in a larger hydrogen demand for HS2.
With the above hydrogen demand and the intermittency of wind power, we can estimate the amount of energy required to cover the intermittency period. This will help us rationalise and decide on the storage volume and storage type, which are dependent on the amount of hydrogen that can be stored, so that the grid's dependency is minimal during the intermittency period.