Abstract
The primary aim of this paper is to expose the significant impacts of AI integration in intelligent energy consumption methods. Notably, the paper has given an insight into the essential factors that have affected the project of AI in the energy departments globally. Besides, creating a relationship between the benefits as well as the requirements from the economic level. But more significantly, the essential sections of the political economy and demographic factors. Therefore, AI integration will play an essential role in elevating the economies and increasing sustainability.
Introduction
The increased growth of the human population has increased the demand for energy consumption. In the past century, traditional forms of energy were applied that could impact the environment. As such, resources have been depleted, resulting in more challenges in terms of energy consumption because of the global warming pollution effect. As such, various scientists have invested in the innovation of new energy resources. For example, the green energy world resources have constantly improved and created more sustainable energy in the environment. There are many other options discovered though the population increment has limited and restricted many energy options. These challenges and the constant development of technology have led to the discovery of more energy resources. Although the world is becoming unsustainable through environmental conservation and depletion of natural resources, there are still options for developed intelligent energy.
Current State of Energy Consumption
Traditional
Energy consumption has been a topic of discussion over the past because of its impacts on the current world. For instance, the structures and elements of the past energy methods mainly relied on natural resources. It was therefore challenging for the world to integrate such options to the current sources. Despite the current modern methods, their rural regions in the world haven’t implimented the current modern methods of energy consumption. Therefore, the topic is increasingly becoming a key concern in a significant number of regions across the world. United Nations has also come up with better ways of applying renewable sources of energy to many economies. However, the developing states have a significant percentage of people who are still not connected to renewable energy sources.
Several factors have impacted the growth of economies in terms of renewable sources of energy. The current energy consumption methods have only been applied in the developed economies and some segments of the developing economies. In the 21st century, the economies still applying traditional energy sources have been affected by the political-economic structure. Issues like corruption and embezzlement of funds have been the main reasons some economies have been stuck on ancient energy resources. However, international organizations like World Bank have created better options and funded many economies in the mission, and plan to elevate people from poverty by creating better energy resources. Therefore, ancient energy consumption is still applied in most countries globally.
Modern
International organizations have pushed the agenda for better energy consumption methods. The top economies like the USA, China, and Russia have invested heavily in the current energy consumption methods. A significant number of economies, even the developing ones, have created agendas on a mission to deploy the current technology on energy. As such, it is a process that has been integrated into a few of the developing economies. Despite the consumption rates deployed in the economy, there was a significant impact on growth. The constant changes in the energy sector have highly impacted how energy is consumed. For example, the growth and advancement of economies have both positively impacted the economies. Hence, creating and integrating the approaches has become a challenge in many economies. AI integration has been introduced as one of the best technologies in enhancing better energy consumption to reduce the depletion rate of natural resources.
In the modern world, every economy is working towards achieving a suitable energy resource. The primary goal is to enhance environmental conservation and sustainability. Despite the significant economic transitions, it has still become an achieved dream in most of the economies. Research by Zhang et al. (2020) has affirmed that the current energy consumption methods are costly. The primary reason is that they are constantly because of the updates in technology every day. Artificial intelligence in the energy sector has played a significant role in the primary power plants in the world. Therefore, AI technology is expected to take the world economy to the next level, depending on its implementation.
Factors Affecting the AI integration in Energy Consumption
Technology
Technology is one of the most significant factors that can enhance the growth of the energy sector globally. Tech will shift most of the energy plants in the world hence creating better energy solutions. The major challenge is that the level of technology advancement varies from one economy to another. This is therefore expected to be a massive challenge in the implementation process of the whole process. AI integration is one of the essential revolutions in the energy sector globally. Many researchers have argued that it is essential for international organizations to ensure that all the economies operate at the bar for the integration to be incorporated well into the current energy consumption methods (Xiong, 2020). The central question is whether the current or modern AI methods will affect the supply and demand of energy in the economies where they will be implemented. Many economies are left with no choice other than doubting the everyday uses of energy compared to the past. Various suggestions have been applied and suggested by the international organization.
The outcome of the smart energy consumption methods has not been confirmed by most of the economies. As such, there is the challenge of creating such options to the current approaches of energy. However, many have argued on the changes and updates that occur systemically. As such, it can be a challenge for developing economies to integrate such budgets. Moreover, the world was changing, and expected outcomes can be challenging to determine and evaluate at times. Therefore, the world must come up with the best ways of ensuring that the methods are assessed.
Economic State
The state of economic growth of a country plays an essential role in assessing the impact of AI methods. Energy consumption is the most integral aspect of the economic growth of any country. As such, any current method to be applied is to be analyzed in terms of the impact it is likely to cause or impact. The May economies under the developing sector have not created many options for better mechanisms of power. Therefore, the implementation of this technology is likely to have a significant impact on their budget. More notably, when calculating the essential requirements for activating the AI integration (Zhang et al., 2020). Many essential factors are needed in the application of AI systems. As such, the variation in the economic factors of every country is likely to have an impact on the energy consumption approaches.
The economies vary based on their budget as well the revenues and GDP incomes. As such, the countries with a lower GDP are likely to get a challenge in implementing AI systems in energy. As such, the countries with a lower power capital income have more basic economic problems, limiting the integration of these approaches. More significantly, the third world countries need other basic needs like healthcare and traditional energy sources to elevate their standards for the current new sources. Furthermore, research by Xiong (2020) has affirmed that economic stability plays a vital role in determining the essential requirements for the energy consumption methods in the market. Therefore, hindering the whole dynamics of transitioning the energy sector to the AI system integrated approaches.
Positive Impacts of AI integration in Energy Consumption
Sustainability
One of the negative impacts of energy is pollution, which can be controlled through AI to make energy sustainable. With the ability to monitor complex systems, AI can be integrated into environmental conservation through monitoring various pollutions, especially from energy production, to make the surroundings sustainable. AI can reduce pollution by removing the CO2 released by industries, help develop environmentally friendly systems such as green transport systems and monitor deforestation. In some cases, AI can help analyze the best applicable green energy system suited in certain areas, thus improving energy consumption, and making it sustainable.
Through commercial monitoring of the energy systems, AI will reduce the energy wasted, thus reducing energy consumption, and making it available to all. Most developing countries always experience power rationing, with much power being wasted; if well managed by the AI, there will be a surplus power supply that can be further stored for future use by the same AI system. Reducing power wastage will lead to less power production, sufficient power supply, and fewer pollutions due to power generation.
Low costs of energy
The increasing population and industrialization have led to increased power demand (Michaelides, 2018). With the cost-of-living shooting, many people cannot afford the power, and for those who can afford it, they feel the impact of its spending. Suppose AI reduces the energy wasted, increases the supply, improves energy storage, and increases green energy production and efficiency. In that case, the cost will be lowered as the energy supply would have been satisfied, and the cost of energy production lowered.
Efficiency
Despite humans having higher reasoning ability than computers, computers tend to be efficient in doing work. Moreover, unlike humans, machines can work for long hours without tiring as long as they are well maintained. However, as a result, most of the energy produced is wasted, especially in large-scale energy consumers such as industries and big companies. Statistically, 70% of the energy produced, 60% is wasted, which accounts for millions that have been wasted. To curb the waste of energy, AI helps to integrate systems to create a good plan for municipalities and big companies to help them manage their energy through various regulations of energy flow. It also helps to forecast the energy to be used, detecting errors before they occur, thus reducing the energy that could be lost during the error of appliance failure.
AI can also help in energy management by controlling and storing renewable and planning sustainable energy in its setting. AI can monitor, collect information, analyze and control energy consumption. Machines tend to work faster than humans; with their proper algorithms, AI machines can handle a large set of data integrated with complex systems and give out a quick solution. These solutions can be implemented and manage energy and reduce the wastage of energy through regulation and rationing as per the required energy in a particular tool or machine. It will also curb unnecessary data distribution, making a machine or tool access power upon request, thus making the system power efficient.
Negative impacts of AI in energy
Expensive
Despite AI serving its masters well, the system tends to be complicated. The system incurs very high expenses during its development. Its development starts from problem analysis, solution finding, prototypes, system development, and staff training. In all these development stages, various costs are incurred, especially in prototypes development coding. The coding stages require experts who have to be compensated highly as they will also play a part in staff training. The equipment and technicalities employed in the system implementation are relatively expensive too.
Job loss
The machine is efficient and makes work easy for the company compared to human beings. Humans have a high intelligence quotient hence they should be solving problems quickly, however machines are reliable as they are programmed and specialize in one task compared to humans with vast knowledge. Furthermore, since machines are fast but cannot be trusted to work independently, they are constantly monitored less staff. This reduces the number of workers needed to perform a particular task, thus rendering them jobless.
Privacy violation
Machines have access to much system data, especially the AI, which has to access all the equipment in a particular setting to analyze, recommend, and manage its energy. As a result, these machines will be given confidential data, which hackers can illegally access. In addition, AI machines can learn new things; they can learn how to violate the system and pose a high privacy violation risk.
Market violation
AI is attributed to various violations that lack contestability and algorithm transparency. In addition, the developers might have hidden agendas that might expose the users to various risks, such as data privacy violations (Reed, 2021). AI is also associated with unfair competition, bias, and discrimination. In other cases, the AI system has caused harm to users or operators, leading to legal prosecutions. The systems might also not meet the market standards, which forces them to redevelopment. The replacement of machines with human in workplaces have also led to legal cases in many states.
System Integration
Apart from system development, there is always a challenge in system integration. During the integration, the staff has to be trained to use the new system, which might seem complicated, and others are not able to use it properly. The system might override the other, be incompatible or damage other coexisting systems leading to significant damage and loss to the company. In addition, the integration might take time, slowing other processes thus affecting the service delivery within that period. The integration can be done by outsourced staff who might also demand high salaries or not be able to understand the existing company system.
Recommendations
Technology Integration
Integrating AI into the energy sector is one of the most challenging processes; as such, every economy planning to integrate this activity must always be ready in terms of technology. Despite the high technological cost, the economy still needs to come up with the essential structures that will guide the production process. The organization in charge of the project will have to test the strength and variability of the economy’s technology. The activity will help the economy come up with the critical and essential needs for the competition of AI integration.
Environmental needs assessment
The environment plays a significant role in identifying the critical needs of the company. Currently, the primary goal of every economy is to create sustainable and renewable sources of energy. The final target is to conserve the environment and have a better system of operation in the future. The AI integration is expected to change a variety of options globally regardless of the country’s economic stability. Therefore, the final process of creating a better system must factor in the significant environmental factors. Notably, include all the required resources and further analysis for a better future (Xiong, 2020). The world is changing, and a vital consideration of the environmental needs will help the project achieve the set objectives efficiently.
Population Growth assessment
Population growth is a challenge in the current world as it has created so many problems in the field of energy. An increase in population is the critical issue that contributed to the depletion of the current energy sources. The firm in charge of the whole project must check on the demographic patters to certify that the process is developed based on the existing and future population trend. The population will also help in coming up with the right plans and requirements for the whole process. The final requirement will be a good plan and budget to accommodate all the people in an economy. The critical target is on how to finally estimate the number of households that will need that integration. Hence, population growth assessment will be vital because it will define all the other requirements in the process.
Political and economic stability
Politics and economic growths are the keys and essential terms in the project. More significantly, how they relate with the entre smart AI energy integration methods. Many economies developing economies have faced the challenge of implementing this technology because of corruption and embezzlement of funds. As such, when implementing this technology, the budget must be well estimated as well the demographic patterns must be considered both in the current and the future. Therefore, the most significant aspect is the value of AI integration to the economy.
Conclusion
The fact that AI integration plays an essential role in smart energy consumption mechanisms cannot be ignored. More significantly, it will increase the efficiency, lower the cost of energy, and increase the speed of interstation of the current energy systems in the market. However, there are associated challenges that are expected with the integration of the new smart AI technology. For example, system integration, market violation, privacy violation, job loss, and expensive integration. Therefore, AI integration in smart energy approaches is the best mechanism to spearhead the energy sustainability goals globally.
References
Michaelides, E. E. (2018). Energy demand and supply. Energy, the Environment, and Sustainability, 35-70.
Reed, C. (2021). undefined. AI, Data and Private Law.
Xiong, Y. (2020). Multi-energy energy hub configuration method containing new energy consumption. 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2).
Zhang, T., Gao, T., Xu, P., & Zhang, J. (2020). A review of AI and AI intelligence assessment. 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2).