Exploring the Concept of an Intelligent Energy Management System
The Transmission System Operator (TSO) is the entity Artificial Intelligence entrusted with the physical transportation of energy from any regional power plant to local households. The TSO has two main responsibilities. First, it has to ensure the security of the power lines through which the electricity is transferred. Second, it has to ensure the constant balance of demand and supply of energy throughout the grid. This last issue has never been so crucial and delicate as it has become recently.
For years, in fact, all power plants have been sized and built to match the demand of energy statistically expected to come from a given area. All the energy produced out of conventional sources such as coal, oil, atomic, geothermal, hydro, or natural gas is fed to the nearest branch of the national or regional grid and from there it reaches the actual households. A number of patterns have been identified over the years to guarantee a constant inflow of energy to the grid in order to balance demand and supply and subsequently prevent both excess and shortage of energy. In the wholesale energy market, the TSO operates to avoid large fluctuations in the energy supply and does that through a number of behavioral codes that all participating companies are called to enforce.
The provisioning model developed out of established practices and, around the 2000s, the introduction of smarter power grids brought the risk of blackouts significantly down thus solving the long-time problem of ensuring grid balance. However, in only a few years, the bold advent of renewable sources radically changed such an idyllic scenario. Renewable sources are uncontrollable by nature and with a growing percentage of uncontrollable energy possibly flooding the grid the risk of damage is unbearably high. The software comes to the rescue and, more specifically, artificial intelligence technologies come to help predict production and control distribution. What the TSO does manually, some artificial portion of code can do automatically.
Intelligent Software to Make Life Easier
A continuously reliable power forecast is all that power plant managers need to know to comply with TSO guidelines and energy traders’ wishes in order to seal better deals. Predictions, however, are possible only in two ways. You have a fortune teller at hand or you’re good at using machine learning algorithms. The role of artificial intelligence is crucial for accurate predictions and to step up the interaction between energy companies and TSOs.
As mentioned, in fact, the biggest difference between a renewable and conventional power plant is the predictability of the output that goes to the power grid. A conventional power plant provides a nearly constant output whereas a renewable power plant is subject to the vagaries of the weather. This is just where the intelligence of software kicks in. Once connected together, a number of independent generation units—even based on different technologies—may be operated as a single, virtualized power plant. Software is used to orchestrate the work of the various generation units, to implement power control, and start and stop units as appropriate for the business and as it may be requested by the local TSO. However, the concept of a virtual power plant goes beyond smart power control.