Deep clean energy data to have a clear business model

Polaris solar PV net news: weiketuo·Maier·sheenboge in the age of big data: living, working and thinking in the revolution of forward-looking noted information from large data storm is change our way of life, work and thought, big data opened an era of great transition. Has been closed, monopolistic and capital-heavy energy industry, has brought the dawn of change data. Data technology application in the field of energy, energy technology revolution and the idea of data depth, will accelerate, including photovoltaic, wind power and other new energy industry development and business model innovation, ultimately usher in the transformation of the energy system as a whole.

Based on the clean energy power plants (here is focused on solar and wind power as the representative of the clean energy) the full life cycle of actions and large data technology processes, the author proposes clean energy data of three-dimensional ecological architecture, that is, data domain, domain, and system fields.

Data fields include clean energy power plant life-cycle (planning and design, construction and inspection, monitoring and control, operation and management, asset valuation, and trading) correlation of all data, includes not only the PV power station operates in real time energy data, should also include emission data, meteorological data and geographic data, as well as some policy information, such as bank lending and power purchase agreements. Work domain will cover data collected from the application life cycle, including the gathering, reception, transmission, storage, processing, visualization, calculation, analysis and applications at multiple levels. System domain includes the equipment and communications layer, the data tier, application tier, and transaction levels.

Clean data is a gradually dug gold mine, through to its acquisition, processing, analysis and applications, their potential value is gradually inject new impetus into the development of clean energy industries. I will detail clean energy data from eight aspects of the application.

1, the clean energy power plant planning and design

By integrating data, meteorological data, geographic data, policy data, financial data, data of power station equipment and other clean energy data, can realize the one-stop planning and design of clean energy power stations.

For example, Geostellar through its online data analysis and search system, provides users with services such as designing, financing, installation of photovoltaic power stations, it raised “hopes to become the largest solar energy resource search engine” this vision; Google Sunroof projects based on high resolution satellite imagery, Google map data, and data around your home to help potential customers interested in rooftop solar installation project, Assessment on their potential after the roof-mounted solar panels and its benefits.

2, power monitoring and maintenance

Clean data service in clean energy generation project of monitoring and maintenance. Based on scenery resources data and the power run data, on power project for run monitoring, and analysis and run efficiency evaluation, for improve project run management level provides support; based on clean energy big data of information mining and intelligent forecast, on power equipment of run management for precision scheduling, and fault diagnosis and state maintenance; based on big data processing of advantage, can achieved from line Shang real-time monitoring to line Xia shipped dimension of timely seamless docking, from remote fault diagnosis to line Xia synchronization maintenance, real achieved efficient of O2O collaborative shipped dimension. Power station monitoring based on data and operations, will radically improve operational effectiveness, safety and quality.

3, equipment evaluation and upgrade

Through real-time monitoring of photovoltaic equipment running, clean energy equipment manufacturing enterprises can run from the huge amounts of data to filter out of key data, and devices for performance evaluation and reliability analysis, statistical failure rate and efficiency, and to proceed on the basis of equipment fault based on data warning, quality value-added services such as upgrades, remote diagnosis, program optimization. In addition, large equipment manufacturing enterprises based on data mining and analysis, to form a production research and development-oriented decision-making information to help businesses take advantage of clean energy equipment development direction, provide data support for product optimization and upgrading, and improve power generation operation safety and quality.

Rating 4, projects and financing

As power plant investment in the emerging funds, trusts and other roles, as well as the popularity of Bank loan for clean energy power station, power station ratings and financing platform will appear. Based on data, including photovoltaic and wind power generation project level, actual status and financial situation evaluation, valuation and risk assessment of the project, providing technical support for project finance, mergers and acquisitions, transfers.

5, forecast and trading

As approved for the transmission and distribution prices with the electricity market continues to open up, the power station will gradually by the integration of electricity sales agents, such as participating in power market trading. At this time, real-time monitoring and forecasting of power generation data will be especially important, when actually electricity generation will be one of electricity pricing reference.

6, the power to dissolve and scheduling

With clean energy power of penetration rate increasingly high, need through on power station for real-time power data monitoring, makes power data participation whole grid of real-time power scheduling among, support grid on clean energy power of optimization scheduling, reduced containing mass clean energy power access of grid run risk, upgrade network source coordination control level, enhanced PV power of elimination na capacity, then achieved energy consumption and energy production distribution of optimization.

For example, on March 20, 2015, with real time solar data monitoring platform PV Leistung in Deutschland, Germany for photovoltaic power capacity, within their national real-time monitoring, which not only gives a photovoltaic system generating capacity during the solar eclipse, also for Germany grid power gives a solid basis for the Eclipse.

Germany solar PV data monitoring platform Leistung in Deutschland

7, policy development and evaluation

Depth of data based on clean energy such as solar data mining and analysis, various regions in China can be realized, photovoltaic solar energy resources construction and operation, regional power grid capacity to conduct a comprehensive assessment and comprehensive, accurate photovoltaic power generation development situation in China and for the Government to develop and improve solar support policies and industry standards provide technical support. In new energy policy developed process in the even in developed zhiqian, through analysis PV big data, completed depth data mining and the analysis, then judge how effective to developed new energy policy programme, to reduced even avoid policy introduced Hou of errors, improve policy implementation efficiency; in new energy policy implementation process in the, through PV big data can established sound feedback mechanism, timely accurate to get new energy related data information, further to based on on data of in-depth analysis, can effective to assessment new energy policy of implementation effect, Policy errors to be corrected. PV into full play the usefulness of the data, new energy will be able to help policy makers to better understand which stimulates behavior, and what kind of environmental policy and regulatory changes will be more realistic and effective.

For example, Germany when in an effort to promote the development and application of renewable energy, the use of new energy generation and family feedback data meter, developed viable incentive policies, adjusted the new energy subsidies, increased investment in new energy and smart grid infrastructure, so as to realize the purpose of optimizing the allocation of resources according to demand.

8, planning and supervision

Based on clean energy data accurate demand oriented model of the new energy plan can be established, and promote collaborative integrated planning model, government scientific decision-making level of material planning for new energy. In addition, use of clean energy technology in energy regulation in the role, promoting the new pattern of energy regulation, establish transparent and effective modern supervision and management network system, improve energy efficiency and effectiveness of regulation.

Like, construction in the of national PV power public data platform, will achieved on has built PV power project full access, building can full reflect PV power project quality, and technology, and performance of public big data platform, analysis assessment PV power General technology and the run status, to for national and the place Government introduced policy provides full of facts according to, achieved on PV power construction and long-term run of regulatory, guarantees PV industry ordered health development.

In short, clean energy data can drive the development of clean energy industries, depending on their business value. Clean energy access to data is important, but control data is not representative of future entrance; clean energy data is really value, need to have a clear and well-defined business model, thus further promoting the application of large data in the clean energy industry.

Original title: clean energy data to have a clear business model

Posted in Solar Charger.