The energy industry needs new ideas to deal with changes brought about by artificial intelligence and grasp the opportunities it brings.
The impact of the digital economy in financial and trade fields has been very obvious. Next, the energy industry will also be changed from several aspects such as commerce, supply, management, market analysis, and security. Although some progress has been made in the development of artificial intelligence, it is not difficult to see that they will bring revolutionary changes.
Artificial intelligence is driving the fourth industrial revolution. It will increase the predictability of the energy industry and optimize its productivity and management capabilities, bringing unprecedented opportunities. Artificial intelligence integrates the advantages of human beings and breaks through its limits. The energy industry needs new ideas to deal with the changes brought about by artificial intelligence and to grasp the opportunities it brings.
The fourth industrial revolution will link humans and artificial intelligence in various platforms. Facing the powerful learning ability of artificial intelligence, creative imagination will be the only advantage of human beings. In fact, the development of a successful artificial intelligence system needs to solve three major problems, computing power, available data and imagination, and the latter is often the most difficult to achieve.
Business and supply intelligence for energy production
The future development of the energy industry lies mainly in optimization and forecasting, and artificial intelligence can provide unique solutions for energy production, energy grid balance and consumption habits. It is not difficult to predict that artificial intelligence will become an important part of the energy industry and be applied to producers, transmitters and consumers. Artificial intelligence is an application process of self-learning and calculus, rather than a method of programming that mimics human work. It is capable of bringing together human capabilities such as visual perception, comprehension, communication, and adaptability, while overcoming human limitations and bringing these advantages together. The current computer combines large-scale and rapid data processing functions.
This provides new opportunities for the energy industry. Taking the oil industry as an example, many oil companies have begun to transform their businesses in light of the world’s declining dependence on oil. Under this trend, they need to make profits in the oil market, need to optimize the production process of fossil energy, and more accurately grasp the interests of customers. French Total is working with technology giants such as Google and Microsoft to develop digital technologies in the energy sector, especially artificial intelligence. At present, Total's engineers are working with top software developers to discuss how to apply complex algorithms to the oil and gas field and optimize exploration, production, and sales processes. BP also invests in the development of artificial intelligence technology in an attempt to combine technical data with natural environmental data to optimize drilling operations.
The production of renewable energy is growing rapidly. With the development of technologies such as wind power, solar energy, and hydropower, these energy sources are becoming more and more popular and their economic benefits are getting higher and higher. However, the biggest challenge for the renewable energy industry is that renewable energy production is intermittent and its production depends on weather conditions such as wind or sunlight. Some studies have also pointed out that climate change may cause a huge change in the distribution of global renewable resources. This means that once energy demand soars, renewable energy sources may not be able to meet demand, so many countries need to adopt multiple strategies to fill the gap in renewable energy supply.
At the same time, the consumption patterns of consumers are also difficult to predict, which has caused instability in supply and demand management as well as in the power grid. The renewable energy industry needs an intelligent technology that can ensure that supply and demand are always in balance to solve energy flow forecasting and management problems.
IBM plans to introduce a new product called Deep Thunder, which will provide accurate weather forecasts with a resolution of 0.2 to 1.2 miles. This technology integrates dozens of forecasting models and collects a lot of weather, Environmental, atmospheric conditions and data sources for the operation of solar power plants and grids. IBM has also conducted extensive collaborative research in the field of renewable energy forecasting. More than 200 projects use its solar and wind energy forecasting technology and work with the US Department of Energy to use artificial intelligence to optimize clean energy applications. IBM claims that its artificial intelligence weather model is more accurate than the solar and wind energy forecast models.
Smart Grid Management
Artificial intelligence will be the core of the future smart grid. At present, the power grid company has configured related technologies in the grid fault alarm system. The artificial intelligence technology will continue to collect and integrate data from millions of smart sensors, and learn autonomously from the patterns and abnormal phenomena of large data sets. Make timely decisions and allocate energy resources in the best possible way.
In terms of demand, artificial intelligence technology can continuously monitor the supply and demand of smart meters and sensors in homes and businesses, measure power flow through the grid in real time, enable operators to proactively manage and avoid disruptions, and modify power usage during off-peak hours. Relax the grid's workload and reduce consumer prices.
On the supply side, artificial intelligence can assist operators or governments in changing energy mix, adjusting fossil energy use, increasing the production of renewable resources, and minimizing the natural intermittent disruption of renewable energy sources. Producers will be able to manage the energy output generated by multiple sources in order to match changes in social, spatial, and temporal needs in real time. Artificial intelligence can also use algorithms to balance the grid, coordinate joint operations in the event of errors or hackers, self-repair the network, and predict production and consumption data.
Google's recent application of artificial intelligence technology has been proven to improve power management efficiency. It estimates the load of data centers, optimizes cooling systems, and manages equipment more efficiently according to the estimation of its machine learning algorithms. Finally, it will use electricity. The amount was reduced by 15% and Google saved hundreds of millions of dollars in a few years. The National Grid of the United Kingdom has also started to study how to apply artificial intelligence, make full use of renewable energy, save costs, and balance the energy supply of the British National Grid. The National Grid of the United Kingdom has a large amount of data for artificial intelligence to learn and predict. The goal is to reduce national energy consumption by 10% through artificial intelligence.
Using Artificial Intelligence to Analyze Consumption Patterns
In the field of energy, the high value of artificial intelligence is reflected in demand management, because artificial intelligence can help energy companies understand the consumption patterns of end customers downstream of the industrial chain. Billions of people around the world, each person's consumption patterns are different. Understanding consumers’ habits, values, motivations, and personalities helps to further strengthen the balance and effectiveness of the market, and can also formulate policies more effectively.
Consumer choices and opinions have a huge impact on the energy industry. By studying energy consumption patterns, energy companies can more specifically design products, manage energy consumption, and even optimize consumer behavior. In general, family customers prefer to express their preferences directly. Therefore, energy companies need to build a platform for connecting consumers. For artificial intelligence, the more consumption data, the more mature the self-learning program.
At gas stations in New York and Chicago, BP also began deploying fuel pumps called “mileage” artificial intelligence systems to enhance consumers’ interactive experiences. While refuelling, Mileage will greet consumers, provide small entertainment, offer discounts, and connect consumers to social platforms. In addition to understanding consumer spending patterns, this interactive intelligence technology can change consumers' perceptions of traditional gas stations and attract them to secondary consumption. In the electricity market, consumers will generate data streams on the grid. At present, some suppliers have already promoted the installation of smart electricity meters to collect data streams in real time. This not only helps predict network loads, but also predicts consumption habits.
Network security problems that accompany the digital economy
The application of artificial intelligence in the energy industry will optimize the energy industry. At the same time, it will also form a full-industry-chain network that will link various energy infrastructures and further the Internet, but what is derived is the issue of cybersecurity. With technological innovation, major changes are taking place in the energy market structure and network security. As cyber threats continue to evolve, infrastructures are increasingly vulnerable to disruptive or destructive attacks. With regard to cyber security, all energy fields are spared. Prolonged interference may affect economic and trade, industrial development, and social stability.
Artificial intelligence links energy networks together, and the weakest part is the various connection points in the energy network. The difference between an energy system and other information systems is that when it is attacked, it cannot easily leave the network because it may cause other supply security problems, such as power cuts or even outages. In the case of cross-border impact, once a challenge arises, it is no longer limited to the operator or a single country.
In the energy sector, the focus of cyber security includes stable supply, integrity and confidentiality. Taking the power market as an example, stable supply and integrity are the most important during power generation and transmission. Data errors or delays can result in equipment misconfiguration and ultimately affect system reliability. As for advanced energy facilities, the confidentiality of customer's personal data is crucial. In the nuclear energy field, cyber security is part of nuclear safety. Ukrainian power grid events in 2015 demonstrated the potential disruptive impact of cyber attacks on the power industry.
Cyber security is a problem that accompanies the digital economy. Its risk to the energy infrastructure is like a flood or a fire. Both supply and demand are affected. Most energy companies are involved in public services. They must regard the network as a core business risk, increase their awareness, establish a strong strategy for technical and manpower network resilience, and adopt a universal cross-departmental cyber security framework to help identify key areas of cyber risk management and identify the need for System protected at all costs.
The government must also supervise network activities, introduce standards, support information sharing, and encourage companies to focus on cyber-risk issues. At the same time, cyber security talent pools need to be cultivated. The demand growth rate is more than twice as fast as that of all other information technology workers. . The insurance department must monitor cyber risks, focus on managing emerging and changing risks, and develop appropriate cyber insurance products to better understand how cyber incidents affect existing portfolios. When analyzing energy industry information in detail, the insurance department must help companies better quantify cyber risks.
In these areas, artificial intelligence will play a key role. Technology companies can play a supporting role in innovation by embedding security functions into the products being developed and delivered. Relevant departments can also use artificial intelligence to monitor cyber attacks, specialize in risk analysis for the highly interdependent energy sector, and formulate effective governance plans and effective network response frameworks to ensure that they can quickly and consistently achieve consensus in an emergency situation. The response.
Europe Type Manual Folding Machine
Manual Folding Machine,Metal Folding Machine,Precision Manual Folding Machine
Yancheng C&J Machinery Co., Ltd. , http://www.chlathemachine.com
没有评论:
发表评论