Using AI for Decision Support in Energy Markets

Using AI for Decision Support in Energy Markets

12-Mar-2018 by Trevor Townsend

Energy Markets are awash with data, gushing from smart meters, the grid, the market operator, financial markets, and not to mention the 1000’s of Internet of Things sensors. Many companies are involved in delivering energy to end customers and all need to make complex operational, pricing and investment decisions on a daily basis. Decisions  to keep the network healthy, attract or retain customers and meet the demands of the future.

Big data, machine learning and artificial intelligence are all technologies that are now being deployed to create the Decision support systems (DSS) of the future.  DSS use data to facilitate decision making. First acknowledged in the 1960s, today recognized as an integral component of a successful business.

Test, Measure, Learn. Data Driven Decision Making; leading to better management and operational decisions.


The need for DSS

As technology advances industry, the demand for decisions has increased. Overload and distortion of information are common. Computerized, well-designed evidence-based systems, improves decision quality, and enhances the overall decision-making process. A pioneering example of how the use of data in decision making is advancing, Google’s Oxygen Project, uses big data to analyse the managerial impact on their organization. However, what we are interested in is how advancements in the decision-making process could impact the energy sector.

Energy Markets

The world is currently in an accelerating energy transition. The way in which energy is produced, consumed and distributed is changing dramatically. The scarcity of natural resources, the increasing emphasis on decarbonizing the energy system, has resulted in industry making tough decisions. For example, some operators are already investing heavily in renewables and embracing technology.

Artificial Intelligence (AI) will create an environment where data can be analyzed and visualized in new and exciting ways. Creating user-friendly data dashboards, opening the door to fast, agile decision making. Highlighted below are functions were AI will play a considerable role.

Determine the feasibility of green energy products-Identifying and evaluating a site is complex. Many factors feed into the evaluation of how successful a site can become. Site viability, supply potential, energy demand, project finance, cost estimates, and profitability analysis. To be effective, it requires substantial labor resource, data mining, and expertise.

Assist with short-term supply forecasting and trading decisions- energy forecasting is the process of applying statistics and machine learning to make predictions of the future energy demand/supply. Most utilities have developed models over an extended period during economically stable times. Today, that stability is being challenged with the expansion of smart grid projects. And therefore, forcing utilities to make wholesale changes to the modeling process.

Assist with the determine complex product pricing such as industrial energy contracts-Energy suppliers are changing the way they buy energy and transport it to your business. The number of tariffs is on the rise. Self-sufficient energy generation through solar is creating new markets, and the potential to sell back to utilities. As a result, it’s becoming increasingly complicated to price in energy contracts.

Static data is no longer an option. AI will create a fluid, agile data environment, that will be essential to make evidence-based decisions in an ever-changing marketplace. With that in mind, Startupbootcamp Energy Australia selected Cognitum to our Smart Energy accelerator program, to help drive better decision making in the energy sector.

Cognitum is an online AI for Human Intelligence Amplification In real-time, it amplifies human intelligence in cognitively demanding tasks for a better decision making in industry. The unique value provides the possibility to perform research on large data sets online. In essence, the platform uses the power of big data to allow anyone to become a data scientist and with that, visualize data in a user-friendly manner, and ultimately make effective informed decisions with real-time fluid data.Their technology has already seen success in Clinical Decision Support, Fraud Detection, and Collaborative Ontology Engineering.  

Cognitum changes the fundamentals of data interaction and analysis. And, in turn, will transform the way decisions are made in the energy market today.