The energy sector has been characterized in recent years by a crisis that affects the globe. As fossil fuel-based energy production decreases in popularity due to its negative effects on the environment and human health, other means of production are added to the grid. Nevertheless, the new methods, with emphasis on renewable energy forms, are not fulfilling the needs of a population highly dependent on electric power, nor are they easily integrated into outdated grids.
As the issues related to grid performance and energy optimization grow, organizations seek to implement solutions enhancing the performance of their assets and control over them. With climate change bringing more natural hazards, such as heat waves or harsh rainy seasons, and a growing number of energy production means being integrated into the grids, it is even more important to have real-time full-knowledge and predictions on asset conditions and capacity. In this article, the hurdles of the 21st century grids, and why predictive and monitoring systems have become key in energy asset management, will be discussed.
The New Paradigm: Increasing Energy Demand and the Integration of New Energy Resources in Grids
Society is highly energy dependent, and the tendency is for electricity usage to increase. This creates a complex situation. On one hand, there is growth in energy consumption and dependence on it. On the other hand, energy production based on fossil fuels is one of the biggest reasons for the climate crisis. While the focus is on substituting highly pollutant fonts with eco-friendly resources, there should be more attention to the management of all assets.
One of the solutions to providing sufficient energy, whilst not creating a significant environmental negative impact, are renewable energy options. While the use of coal, gas, and oil as the basis of energy production decrease, renewable sources are growing year after year. This is a tendency supported by governments and organizations all over the world, following the climate hazards resulting from greenhouse gases.
Despite seeming the best existing option, renewable energy sources have their own hurdles associated. Firstly, renewable sources are usually intermittent, meaning that their production constantly varies. For instance, photovoltaic panels are dependent on the weather, and so its production varies and, if at one time it was producing a great amount of power, that can change quickly. The intermittency of the resources is one of the causes for bottlenecks in the grid. As there is no way to control the production per se, the best way is to predict production and manage it in real time.
Moreover, the energy assets are usually old and inappropriate for contemporary use. Over the last century, the grids were designed and constructed to transport energy from the production site to the consumer. Howbeit, the energy flow is not a continuous and unilateral process, as it once was. Nowadays, a greater and diversified number of energy sources are integrated on the grids, and the outdated assets are not adequate nor prepared for this new paradigm.
To ensure the energy needs of society are fulfilled, while trying to achieve the net-zero goals for a cleaner future, and having in mind the existing assets and their conditions, organizations must comply with an active management of their grids.
Data-Driven Decisions for Asset Management
From the moment of its production until it reaches its final consumer, electric power can travel kilometers, even passing borders. A lot of energy is lost on the way, sometimes the grid is not using its full capacity, other times the energy flow is above the recommended limit. These are some examples of the issues that happen daily in transmission and distribution lines. The biggest problem of them all, however, is that sometimes the ones managing the lines are not aware of the issues instantaneously.
Thus, monitoring systems are key to enhancing grid performance in multiple manners. Firstly, real-time monitoring allows for data-driven decisions and to use the full potential of the grid or, on the contrary, preventing the load from passing the grid recommended capacity. This kind of preventive action is important to maintain the grid’s health and avoid accidents, while using the assets full capacity.
The importance of the proactive management of energy assets is a concern also shared by institutions and governments. To illustrate, the Federal Energy Regulatory Commission (FERC) Order 881, being put in place in the U.S., asks for transmission line owners to be transparent on their asset usage. A common service sought by companies to fulfill this monitoring need is the dynamic line rating (also known as DLR), a tool that allows for grid management specialists to make appropriate decisions according to real-time data. So, instead of having a defined load of energy, based on means and statistics, it is possible to have a dynamic flow, based on the conditions of the assets and the external environment.
As stated before, intermittent fonts have been added to the grids, so the issues with excessive or low loads happen more frequently. Managing the grid for it to have the best load at all moments is not just a way of optimizing the grid performance by using the full capacity of the grid, but also to protect and improve asset lifespan, as a higher load than recommended causes damage to the infrastructure.
By forecasting weather conditions and energy demand, for instance, the enhancement of the grid performance could be the result of proactive practices toward the future. Being ready and informed about the hereafter allows for strategic resource allocation and an improved operational efficiency. Especially in times when extreme weather events, which influence the asset condition and performance, as well as some energy production resources, are more frequent and severe, looking ahead is the best way to manage the grid, and use its full capacity in a safe, controlled, and reliable manner.
One of the challenges in applying a proactive management approach is the lack of mediums and resources providing real-time data. The new challenges brought up in this article have influenced a new wave of research seeking to solve them. Technologies associated with real-time monitoring are being refined, as a result of the market’s needs.
Recent and sophisticated technologies, such as digital twin models, artificial intelligence, and machine learning are being used by certain companies to provide full knowledge of assets to support decision-making. For instance, the software developers from Enline, by applying physical and mathematical calculations with other external data, can use these technologies to provide forecasts that aim at a future-driven management, as well as real-time information. While using digital twins of the assets, it is possible to acquire the data with no physical presence, such as sensors. So, the solutions for a worldwide administration of electric grids will lean into this genre of solution.
Future-Proof Electric Assets
Electric asset managers have been adapting to the new times, characterized by a more drastic dependency on energy, new ways of producing energy being connected, and climate change influencing drastic climate events. Making the existing grids’ performances better is a challenge, but there are solutions.
Technological advances are part of making energy management easier, better, and more reliable. Looking into the future, and having a realistic approach to the issues that are to come, such as the aging of assets, measures should be taken in the present.
—Gilda Mariana Costa is a marketing manager with Enline.