Greenwich Cloud Service

Mesoscale public data service

Apply mesoscale WRF model for mesoscale modeling. With multiple data sources, select the most applicable re-analyze material-drive mode in each area for reliable result. This is the process of initial field and boundary restriction selection.
Adopt assimilation technology to make the most of observation materials to form accurate mode initial field, so as to optimize simulation effect.
Perform optimized calculation process according to local conditions. The weather characteristics varies in the vast territory of China. In the calculation, the most approximate mode parameterized scheme and microphysical process are selected according to the local weather process. This is the process of simulation process adjustment.
Perform post-operation on simulation results. According to the error regularities derived from terrain and land-ocean distribution in various areas, different methods of post-operations are adopted in sub-areas to provide error level of mesoscale wind speed.

Macrositing and met mast management

Based on domain public data, realize macrositing by automatically selecting representative recommended mast location, height, and preferences. Analysis is applied from the following dimensions: spacial scope representative, elevation representative, roughness representative, mast functionality, and special terrain effect.
Monitor met masts in real time, automatically collect data for analysis, and report anomalies.

Standardized met mast data processing

Enhance engineers' work efficiency by standardized mast data quality judgement, data repair, data correction, and long-term correction.
Quantify risk and automatically recommend the best mast data management means to enhance mast data analysis level.

CFD modeling analysis (CFD and WAsP)

Developed from OpenFOAM, the CFD simulation model GREENWICHCFD® masters the core technology.
Support high-performance calculation (HPC) to output wind resource result in a faster and more stable way.
Through study on an awful lot of ideal experiments, academic research cases and post-assessment projects, ensure the accuracy and reliability of GREENWICHCFD® simulation.
Establish optimized model parameter library to accumulate experience of improving simulation accuracy.
While accurately simulating wind resource, focus on the accuracy of turbine security parameter simulation to ensure stable operation within ideal life span.
Two calculation approaches, linear model and CFD model, work together.

Turbine location optimization

Static turbine layout optimization with mixed turbine models, dynamic turbine layout optimization considering wind farm coordination and control characteristic, and over-sea turbine layout optimization considering wake flow and neatness of layout.
According to the wind farm condition and interplay of multiple elements, perform wind farm design optimization with the following properties: customized optimization goal, mixed turbine models, and non-quantification (such as AEP, NPV, IRR).
Adopt high-performance calculation system (HPC) to enhance calculation efficiency in optimization, while other optimization softwares in the wind power industry tend to be time-consuming.

Wind resource post-assessment

Establish post-assessment data library based on big data technology, which boosts the data processing efficiency by tens or hundreds of times.
Full-scale post-assessment based on EBA calculation, including design and product post-assessment.
Summarize wind resource calculation characteristics and synchronize the data into expert system for model recognition.

Turbine foundation optimization

Based on national standard, support foundation structure calculation report export and turbine load working condition verification to eliminate risk in foundation structure design.
Based on intelligent algorithm for best foundation design, auto-group all turbines in the wind farm and customize the design for best foundation scheme.
Generate foundation design report and construction drawings by one-click, realizing quick design of expanded and pile foundation and anchor bolt and foundation ring connection.

Route and platform design and optimization

According to various requirements of different projects for platform component installation, seek for best platform scheme automatically by machine learning. Optimize acquired land area and platform cut and fill quantity as ensuring placement and hoist of main components.
Bearing the entrance point, terrain, restriction area, and transport vehicle requirements in mind, the route optimization level and route selection efficiency are significantly enhanced.
Relying on machine learning algorithm, realize integrated optimization of wind farm route and platform according to platform and route schemes, remarkably decreasing wind farm construction engineering quantity.
Route design drawings are generated by one-click with automatic drawing subdivision and drawings of plane, cross and vertical sections.

Power line optimization and substation siting

According to the requirements of terrain, substation location, restriction area, and existing road network, select the most economical wire optimization scheme (including three forms as aerial, cable, and mixed form) to reduce engineers' work load on grouping, comparison, and determination.
According to terrain and weather condition in wind farm, optimize tower layout automatically with standard tower type, significantly improving work efficiency. Check power lines according to national standard and provide data management service for customized tower.
Optimize substation siting scheme according to power line, route, and output circuit. Recommend several available siting options with cost of power line and route, helping field work siting design.
Generate power line design drawings by one-click for feasibility study and project bidding.

Standardized design process and feasibility study report generation

Based on wind farm PBOM list and price library, combine the process of design, purchasing, technology and post-assessment.
With the help of Greenwich feasibility study design, the report authoring (including adjustment) within office is able to be completed within 3 days by one engineer. The engineer's intelligence is saved for other valuable work by this efficiency design.