IBM has announced that it is deploying the full force of its researchers in laboratories around the world in a 10-year initiative to support China in transforming its national energy systems and protecting the health of citizens.
Dubbed "Green Horizon", the project sets out to leap beyond current global practices in three areas critical to China's sustainable growth: air quality management, renewable energy forecasting and energy optimization for industry. 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.
One of the first partners to come on board is the Beijing municipal government. Through a collaboration agreement, the two parties have agreed to work together to develop solutions that can help tackle the city's air pollution challenges. The collaboration will leverage some of IBM's most advanced technologies such as cognitive computing, optical sensors and the internet of things all based on a Big Data and analytics platform and drawing on IBM's deep experience in weather prediction and climate modeling.
China's economic growth over the past several decades has raised the living standards of hundreds of millions of Chinese citizens and led to China becoming the second largest economy in the world. However, the resulting environmental impact, particularly air pollution, has become a priority for the Chinese government and a matter of global importance.
Global urbanization is creating air quality challenges for all major cities around the world. In China, where cities have been the engines of much of the country's economic growth over the past decade, the government has launched the "Airborne Pollution Prevention and Control Action Plan" as it moves to safeguard the health of about 700 million people living in urban areas.
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 percent 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.
With accurate, real-time data about Beijing's air quality, the government will be able to take rapid action to address environmental issues by adjusting production at specific factories or alerting citizens about developing air quality issues.
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 is renowned for its variability. It enables utility companies to forecast the amount of energy, which will be available to be redirected into the grid, or stored — helping to ensure that as little as possible is wasted. It increases the viability of renewable energy, helping the Chinese government to realize its objective of getting 13 percent 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 wind, solar 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 percent more alternative energy (enough for 14,000 homes) into the national grid. With a prediction accuracy of 90 percent proven on Zhangbei's wind turbines, it is one of the most accurate energy forecasting systems in the world.
China's economic growth over the past 10 years has led it to becoming the biggest energy consumer in the world. As part of the transformation of Chinese industry, the government has committed to reducing the country's "carbon intensity" by 40-45 percent by the year 2020, compared with 2005 levels (equivalent to 130 million tons of coal per year).
To support these goals, IBM is developing a new system to help monitor, manage and optimize the energy consumption of industrial enterprises — representing over 70 percent 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 system will be valuable for guiding decisions about optimization and investment in China's most power hungry industries such as steel, cement, chemical and non-ferrous metal.
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.