Predictive Maintenance in Software Systems Using AI
Date: 13/11/24
By: Krzysztof Lewczuk
Before the Russian invasion of Ukraine and subsequent war, many people expected the energy crisis to last around six months. Now the majority believe that we’re in it for the long game, expecting price volatility and disruption for in excess of two years. But with disruption comes the opportunity for change and new business models and there was a guarded positivity as to what that might mean for pushing forward with the agenda on renewables and storage, and the technology-led transformation needed to support them.
The importance of finding new and ecologically sound methods of energy generation and storage to swerve the Russian energy curveballs is clear. Finding the answers to ensure there is a sustainable, secure, and affordable long-term energy system were consistent themes discussed at length across the two-day event.
The energy market is currently characterised by new market entrants presenting new types of power generation alongside the existing market players who are also diversifying into new asset bases.
The net result of increasing complexity of asset portfolios (whether new or existing players) is the increasing need for real-time reporting, the need for faster access to real-time data and analytics – and the ability for people in an organisation to have access (ideally on a self-serve basis) to trusted data.
In addition, as more organisations move into intraday trading, trading volumes naturally increase and that also brings new data challenges, as well as presenting a question mark over whether existing IT architectures are really fit for purpose to support the new paradigm.
Organisations looking to support new assets and higher trading volumes – and the resultant reliance on real-time data analytics to fuel the success of diversification – puts the spotlight firmly on technology and specifically whether new functional requirements are supported by the current architectural stack.
In response, many organisations are moving from an application-centric situation to one where best-of-breed solutions are being employed for specific requirements. As such, the architectural landscape is becoming more modular. This brings with it the opportunity for agility and a move away from reliance on legacy systems and their constraints.
Innovation can mean moving forwards with machine learning platforms to predict energy and trading prices, which are now starting to be developed and used. Algo trading has been growing for some time but there are also innovative contract management solutions being developed to replace spreadsheet-reliant systems still in use.
Data issues have been amplified by the current market conditions. Organisations who can make best use of data through analytics, strategies, systems, and skillsets will be well placed to drive change in their organisation.
Data per se is not the new oil. If it is siloed it is not the new oil, nor is it if that data is not accessible or requires further manipulation before making good trading decisions.
Data requires an IT infrastructure and governance to support it, processes and tools to manipulate it and skillsets available to deliver its true value.
Digiterre has been enabling rapid technology-led transformation for clients such as EnBW, Uniper and RWE (to name a few) for over 22 years, solving some of their toughest business problems. You can read our client success stories or if you are ready to discuss your challenges and find out how we can help email [email protected]
Date: 13/11/24
By: Krzysztof Lewczuk
Date: 05/11/24
By: Krzysztof Lewczuk
Date: 30/10/24
By: Krzysztof Lewczuk
Date: 24/10/24
By: Krzysztof Lewczuk
If you would like to find out more, or want to discuss your current challenges with one of the team, please get in touch.