IBM Research launches Green Horizon in China

IBM has launched a 10-year research initiative to support China in transforming its national energy systems.

Dubbed "Green Horizon," the project sets out to leap beyond current global practices in three areas critical to China’s sustainable growth: renewable energy forecasting, energy optimization for industry and air quality management.

Led by IBM’s China Research laboratory, the initiative will tap into the company’s network of 12 global research labs and create an innovation ecosystem of partners from government, academia, industry and private enterprise.

Renewable energy forecasting

The Chinese government recently announced increased investment in solar, wind, hydro and biomass energy in a bid to decrease its dependency on fossil fuels. To support the objective, IBM has developed a renewable energy forecasting system to help energy grids harness and manage alternative energy sources.

The solution combines weather prediction and Big Data analytics to accurately forecast the availability of renewable energy, which can be extremely variable. It enables utility companies to forecast the amount of energy that will be available to be redirected into the grid or stored, helping to ensure that as little as possible is wasted.

IBM says the system increases the viability of renewable energy, helping the Chinese government to realize its objective of getting 13% of consumed energy from non-fossil fuels by 2017 and enabling the construction of the world’s biggest renewable grids.

Based on IBM’s Hybrid Renewable Energy Forecasting (HyRef) technology, the solution uses weather modeling capabilities, advanced cloud imaging technology and sky-facing cameras to track cloud movements, while sensors monitor wind speed, temperature and direction. It can predict the performance of individual renewable energy farms and estimate the amount of energy several days ahead.

The system has already been rolled out to 30 solar, wind and hydro power sources. The biggest deployment is at China’s largest renewable energy initiative – the Zhangbei Demonstration Project managed by State Grid Jibei Electricity Power Company Limited (SG-JBEPC) in the Northern province of Hebei. Using the system, SG-JBEPC is able to integrate 10% more alternative energy (enough for 14,000 homes) into the national grid. With a prediction accuracy of 90% proven on Zhangbei’s wind turbines, it is one of the most accurate energy forecasting systems in the world.

"Applying analytics and harnessing big data will allow utilities to tackle the intermittent nature of renewable energy and forecast power production from solar and wind, in a way that has never been done before," said Brad Gammons, general manager of IBM’s Global Energy and Utilities Industry. "We have developed an intelligent system that combines weather and power forecasting to increase system availability and optimize power grid performance."

Energy optimization for industry

To support China’s goal to reduce its “carbon intensity” by 40-45% by 2020, compared with 2005 levels (equivalent to 130 million tons of coal per year), IBM is developing a new system to help monitor, manage and optimize the energy consumption of industrial enterprises – representing over 70% of China’s total energy consumption.

Using a Big Data and analytics platform deployed over the cloud, it will analyze vast amounts of data generated by energy monitoring devices and identify opportunities for conservation. It could be used to analyze data from industrial enterprises in different cities and identify which sites and equipment waste the most energy.

The new energy optimization system for industry leverages IBM’s expertise in regional energy management in China. IBM is already engaged with China Southern Grid to manage the energy consumption of HengQin Island in Guangdong province helping the island to decrease energy consumption, costs and CO2 emissions.

Urban air quality management

The Beijing Municipal Government has become one of the first partners to join the project, agreeing to work with IBM to develop solutions for the city’s air pollution problems.

"China has made great achievements and contributed much to the world’s economic growth over the past 30 years,” said D.C. Chien, chairman and CEO of IBM Greater China Group. “It now has an opportunity to lead the world in sustainable energy and environmental management. While other nations waited until their economies were fully developed before taking comprehensive action to address environmental issues, China can leverage IBM’s most advanced information technologies to help transform its energy infrastructures in parallel with its growth."

The resulting environmental impact of China’s immense economic growth over the past several decades, particularly air pollution, has become a priority for the Chinese government.

"The key to tackling environmental problems is not only monitoring emissions but adopting a comprehensive approach to air quality management and addressing the issues at their roots,” said Lu Qiang, professor at Tsinghua University and Fellow of the Chinese Academy of Sciences. “Initiatives like IBM’s Green Horizon can help by fostering joint innovation across the entire energy value chain."

The city of Beijing will invest over $160 billion to improve air quality and deliver on its target of reducing harmful fine Particulate Matter (PM 2.5) particles by 25% by 2017. To support the initiative, IBM is partnering with the Beijing Municipal Government on a system to enable authorities to pinpoint the type, source and level of emissions and predict air quality in the city.

IBM’s cognitive computing systems will analyze and learn from streams of real-time data generated by air quality monitoring stations, meteorological satellites and IBM’s new-generation optical sensors – all connected by the internet of things. By applying supercomputing processing power, scientists from IBM and the Beijing government aim to create visual maps showing the source and dispersion of pollutants across Beijing 72 hours in advance with street-scale resolution.