One of the key concepts behind Enlitia’s platform and custom solutions is the Algorithm Ecosystem. But what does this mean? Throughout this article, we’ll explore what this concept is, why we apply it to our development process and what benefits it offers.
Before we dive into this core concept, we should first remember some other concepts that work as a base for the Algorithm Ecosystem.
An algorithm is a set of step-by-step instructions or procedures used to solve a problem or accomplish a task. It is a well-defined computational procedure that takes some input, follows a series of instructions, and produces an output. The instructions that make up an algorithm can be written in various forms, including natural language, pseudocode, or a programming language.
An algorithm can be used to perform a wide range of tasks, from simple arithmetic operations to complex data processing tasks. Algorithms are used extensively in computer science, mathematics, engineering, and many other fields.
Some key characteristics of an algorithm include:
Overall, an algorithm can be a powerful tool for problem-solving and computation, with many applications across a wide range of fields.
An ecosystem is a complex and interconnected system composed of living organisms and their physical environment, which interact and influence each other. Ecosystems can be found in various sizes and forms, from small microcosms to large biomes.
An ecosystem consists of many individual parts, each with its own specific function, which work together in a coordinated manner to achieve an overall goal. Within an ecosystem, living organisms play different roles and have various relationships with one another, forming a complex network of interactions that affect the overall health and sustainability of the ecosystem.
Overall, an ecosystem is a complex and interconnected system that depends on the coordinated efforts of many different components in order to produce the best results possible.
An algorithm ecosystem is a group of interdependent algorithms that work together to achieve a common goal or solve a particular problem, adding value to the businesses. Similar to a natural ecosystem, an algorithm ecosystem consists of different types of algorithms and computational tools that perform specific functions and interact with each other in complex ways. These interactions may include sharing data and results between algorithms, combining outputs, or even modifying the behaviour of other algorithms based on their own results.
Just as a natural ecosystem requires balance and optimisation to function properly, an algorithm ecosystem also requires careful design and management to ensure that the algorithms work together in a coordinated and effective manner. This can involve selecting algorithms that complement each other's strengths and weaknesses, optimising their parameters to improve performance, and ensuring that the overall system remains robust and adaptable in the face of changing conditions.
An algorithm ecosystem is a powerful tool for solving complex computational problems that require the coordinated efforts of multiple algorithms and computational tools. By bringing together different algorithms in a unified system, like the Enlitia’s Platform, an algorithm ecosystem can leverage the strengths of each component to achieve a more effective and efficient solution.
Overall, just as an ecosystem is a complex and interconnected system that depends on the coordinated efforts of many different components, an Algorithm Ecosystem working together can be described as a system that depends on the coordinated efforts of many individual algorithms to achieve a larger goal.
Now that you already know what an Algorithm Ecosystem is, you must be wondering: why is this important for me and my business? Applying this concept to a business brings several advantages and benefits, like:
What about some real use cases of this concept? How can an Algorithm Ecosystem deliver more value than the traditional way of developing a platform or custom solution? Here, we want to explore two real-world use cases where we have detected that the added value for the business granted by the algorithm ecosystem was exponentially better than several isolated systems.
Penalties associated with energy markets can be significantly minimised, particularly for renewable energy producers. Traditionally, operational teams and trading teams operate independently, each relying on their own algorithms to support decision-making. However, the Algorithm Ecosystem enables these two algorithms to seamlessly share information, leading to valuable insights for both teams and maximising the company's profit.
The operational team benefits from the Algorithm Ecosystem by quickly detecting failures, thus minimising energy losses. With real-time information on unavailabilities provided by the Failure Detection Algorithm, the trading team can make more accurate power predictions for the upcoming hours and days, resulting in reduced costs associated with deviations and improved trading strategies. Additionally, the algorithm ecosystem enables the trading team to have real-time insights into unavailability, allowing them to adjust their energy bids in real time.
By leveraging the Algorithm Ecosystem, the company can prioritise its workforce based on the most valuable energy, enhancing operational efficiency. Furthermore, the integration of data between the algorithms enhances the overall decision-making process, providing a comprehensive view of the company's energy operations and allowing for better alignment between operational and trading teams.
Anticipating renewable production for the upcoming days is crucial for renewable operators to effectively prioritise their workforce. However, selecting the best power forecast providers can be a challenging task. Different providers may have varying performances depending on the technology (solar or wind) and geographic location. To achieve optimal performance, renewable operators often acquire multiple power forecast sources. Daily, field operators train their own "neural network" to determine the most reliable provider for each site.
By implementing an algorithm ecosystem, it becomes possible to not only identify the best provider for each site in real time but also combine multiple forecasts with real-time data to create a comprehensive and multidimensional model capable of providing more accurate power forecasts. This integrated approach allows for ongoing evaluation of forecast providers and their performance. If a specific provider is not bringing value or if improvements are necessary, the algorithm ecosystem empowers the operational team to identify these issues in real time and make necessary adjustments.
Moreover, the algorithm ecosystem enables the generation of multiple scenarios based on real-time power forecast performance. This ability to simulate different scenarios provides the operational team with valuable insights for making informed decisions. By evaluating different scenarios, the team can optimise workforce allocation, minimise potential risks, and maximise overall operational efficiency.
If you reach this far, then it means that you already know what an algorithm ecosystem is and some of its main benefits. But one other question may remain: what about the synergies of our own Enlitia’s Platform Algorithms? Our platform is built on four main models or algorithms.
The Performance Index is a combination of algorithms that leverage historical data and comparative analysis to assess an asset's energy output. By identifying areas of underperformance and suggesting potential improvements, the performance index helps operators enhance the asset's overall performance and optimise energy production.
Through a combination of algorithms monitoring temperature signals, the health index, helps identify potential issues or anomalies in different components. By detecting problems early, predictive maintenance can be performed, preventing more serious damage and resulting in cost and time savings. The health index also enables predictive maintenance, enhancing the overall reliability and performance of the system.
The Predictive Index is a real-time algorithm that integrates the best power forecast providers, weather sources, and satellite information. By combining these data sources, it accurately predicts the asset's availability for the upcoming days. This enables optimised workforce allocation, minimising downtime, and reducing penalty costs. The real-time nature of the Predictive Index empowers operators to make informed decisions and proactively manage the asset's performance in dynamic operating conditions.
Our Trust Index plays a crucial role in the Algorithm Ecosystem by validating and preparing the data used by the other algorithms. By performing data cleaning, normalisation, and quality control, the Trust Index helps to ensure the accuracy, reliability, and integrity of the data, enabling the subsequent algorithms to generate more accurate and reliable results.
By leveraging the strengths of each algorithm and facilitating data sharing and collaboration, the Algorithm Ecosystem offers several advantages such as enhanced performance, global optimisation, adaptability to changing strategies, utilisation of preceding knowledge, and the ability to simulate scenarios for better decision-making, impacting directly on the revenue.