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Greenwich Overview

This chapter is an introduction to the values and functions of Greenwich platform, and the structure and reference documents of this manual.

Envision Greenwich™ platform is designed for the whole life cycle of intelligent wind farm. It is a platform aiming to overcome challenges in the wind power developing process and secure the best economic indicators of wind power investment.

Greenwich provides the following functions: wind power farm design, mast monitor and management, wind resource evaluation, macrositing, optimization of low-wind-speed wind farms and wind farms at sea, turbine foundation design, platform and road design, electrical circuit design, booster station siting and design, wind farm budget evaluation, economic evaluation, and post-evaluation.

With the delicacy of Greenwich, your wind power farms will be warranted with the following improvements:

  • Design efficiency is increased by at least 50%.
  • Project design cost is decreased 500 RMB/kW.
  • Income from investment is increased by at least 20%.
  • Deviation of production capacity design is controlled within 6% to avoid unexpected investment risk.

Problems in Wind Power Industry

Currently, the wind power industry are facing the following challenges:

  • Design accuracy is not satisfactory, because there is neither standard methodology system for the whole process nor integrated design tool for this system.

    The deficiency or lack of professional management tool in macrositing, mast scheme management, wind resource evaluation, and power production evaluation phases, leads to the low level of wind power farm design, turbine model selection and turbine layout error, obvious power production difference compared with expectation, the performance of some turbines are much lower than the average level in the wind farm, the income from investment is not as satisfied as expected.

  • Closed design loop cannot be realized because lack of standard post evaluation methodology system and professional tools.

    Lack of standard post evaluation methodologies and tools prevents the quantification on the wind farm design level. The design experience and knowledge cannot be collected for optimization of future designs.

    Lack of standard post evaluation methodologies and tools prevents the quantification on the wind farm operation and technology improvement effect. As a result, the continuous optimization of wind farm assets cannot be realized.

  • The vast amount of information required for wind field design is lack of support of big data platform.

    The professional public data required by wind field planning is difficult to be obtained, and its quality is hard to be evaluated. In the early stage of project, especially in the planning phase, the inadequacy of public data evidently impedes wind field plan and process.

  • In order to decrease risk, generally, the wind field designs are retained with over 20% design margin, which results in various levels of design. In a typical wind field design process, the cross-functional cooperation is difficult to be realized, which makes the design process much more complicated. The inter-functional design optimization totally relies on the engineers’ experience, which prevents sufficient improvement on the designs.

Greenwich Features and Values

  • Full-life-cycle solutions for wind farms
    • Effective support for property developers’ core capability enhancement and government agency’s full-life-cycle management on all wind farms. Greenwich plays an important role across the planning, design, production, and management domains of property developers, providing technical scheme management and optimization on macrositing, met mast planning, wind measuring, wind resource evaluation, feasibility study, project design, until commercial operation, which realizes a maximization of investment return.
    • Ecological industrial cooperation based on project solutions: The scattered wind power corporations and agencies are able to work on the tasks in a synchronized project and time dimension. This makes the immediate reaction to customized solutions based on user requirements possible, and reduces the cross-functional and cross-agency operation risk.
    • Promoting the formation of property-to-capital benchmark formation in the wind power industry: With the same reference, the property value measuring standards and ways are established and promoted as industrial standards, which accelerates rational investment and financing schema in wind power industry.
  • Value creation with investment economic indicators as ultimate motivation
    • Aiming at best investment economic indicators in design optimization instead of best theoretical power production, the wind farm design resembles the final construction.
    • Based on the full-process uncertainty analysis model, the influence of various uncertain factors on project investment benefit is quantified.
  • Integrated innovation based on the core intellectual achievements in the renewable energy industry
    • Greenwich integrates the renewable energy industry public data library based on big data platform, providing professional supportive data required in wind power planning and project planning, such as mesoscale weather data, terrain and elevation data, land surface and roughness data, administrative division and satellite map data, environmentally sensitive area data, and full-life-cycle data from design to operation of authorized projects.
    • Greenwich integrates professional mesoscale weather model based on high-performance calculation environment. Relying on data assimilation, sectional parameter combination, and regressional analytic post-processing technology, global wind power map leads the industry with high-accuracy virtual mast data service.
    • Greenwich integrates professional CFD model based on high-performance calculation environment. Compared with other commercial CFD softwares, this model is capable for CFD model simulation with better resolution and precision.
    • Greenwich integrates the plan optimizing engine to optimize the core technical schemes, such as macrositing and met mast planning, micrositing, substation siting, route and power line design, seeking the best performance of customer-specified investment economic indicator.
    • Deep learning algorithm is applied over the wind farm unit project design processes as foundation structure design, route plane, vertical, and cross section design, power line tower arrangement, etc.
  • Knowledge-based engineering (KBE) integrated with experience and wisdom: Sustainable knowledge management system and robust scheme optimizing engine effectively support value creation and capability enhancement.
    • Assistant business unit design, knowledge (regulation) and experience amassment: During the processing of unit business, there are lots of design parameters and models, boundary restrictions and objective judgements. The KBE system simulates objective thoughts according to boundary restrictions and logic process for quick setup, or even one-click setup, on design parameters and models. Through a vast amount of case study, knowledge (regulation) and experience amassment is realized.
    • Optimization on core calculation models of solutions: intelligent core calculation model optimization is realized by the Greenwich platform. KBE offers real-time analysis on external input variation and cross-module iteration result variation. Based on the boundary restrictions across modules, the best parameter in the core calculation model is determined. Through a vast amount of case study, knowledge (regulation) and experience amassment is realized.

Greenwich Cloud Service

Greenwich cloud service offers you the following functions:

  • 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)
    • The CFD simulation model of 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.

Document Structure

A brief introduction to each chapter in this manual is shown as below:

Chapter Name Introduction
Introduction to Greenwich Platform Summarize the problems in the wind power industry, the Greenwich features and values, main functionalities, document structure, and preliminary knowledge.
Greenwich Login Introduce how to login the Greenwich platform.
Greenwich Fundamentals Introduce the public modules and fundamental functions of Greenwich, including project menu, database, tools library, toolbar menu, operation pane, and so on. This chapter guides you to quickly get acquainted with Greenwich interfaces and basic operations.
Wind Resource Arrangement Introduce the application of macrositing and marcroplanning, and demonstrate the steps to select wind farm and turbines in a large-scale scope with reference to interface and tasks.
Planning and Siting Introduce the main modules covered in wind farm planning and siting, and demonstrate the operation and calculation of mast, map, CFD model, turbine model, AEP, and noise.
Post-Assessment Introduce the importance and value of post-assessment, and method to collect data and calculate EBA.
Unit Project Design Introduce the configuration, calculation and optimization of unit project, including turbine foundation design, route and platform design, access plan design, substation siting, power line design, and substation design.
Budget Estimation Introduce the configuration and calculation of wind farm engineering quantity and cost estimation, and how to generate and check the result.
Economic Evaluation Introduce the three approaches to configure and calculate wind farm benefit, and how to generate and check the result.
Feasibility Study Introduce the configuration and calculation of feasibility study report, and how to generate and check the report.