Synengco has been providing customised software solutions to a variety of company end-users from Industry to Government for a number of years. These tools primarily come in the form of decision-support and prediction platforms that help our end-users make more informed decisions about their business domain.
We create and implement software tools and data analysis solutions that help you make better decisions faster – saving you time and resources from the top down.
Methodology
At Synengco, we deliver software projects using well established agile project delivery techniques. Agile project management is an approach based on delivering requirements iteratively and incrementally throughout the project life cycle. This is reflected in the multistage approach to the project delivery and the ability for the customer to redirect or cancel the next stage of the project based on the outcome of the previous stage.
Agile project delivery describes a set of values and principles for project delivery under which requirements and solutions evolve through the collaborative effort of self-organizing cross-functional teams. It advocates adaptive planning, evolutionary solution development, early delivery, and continuous improvement.
In addition to building customised data analytics and software applications, we are also happy to provide training and consulting for the ongoing use and understanding of these products to ensure you have a seamless and fluid experience when using these products.
At Synengco, we welcome new challenges and opportunities to help businesses in their quest for operational efficiency. If you would like to have a chat with us about customised software solutions to help your organisation with critical decision making, please don’t hesitate to get in contact with us.
Some examples of software solutions we have provided for our clients are listed below:
Energy Market Forecasting Tool
The objective of the Market Forecast Tool that was created for our Government client was to develop behaviour-based National Energy Market (NEM) forecasting models that could incorporate machine learning techniques. The models that were designed catered to two purposes:
- Predicting existing power generation assets’ behaviour within the national energy market – using a range of publicly available data, including demand, fuel, price and transmission constraints.
- Forecasting demand met by residential solar and electric vehicles
To provide strategic decision support tools like this to our clients, we leverage knowledge and data from various sources into a single, reproducible model. This is where decision-makers can analyse risks and opportunities and come up with the optimal strategic decision based on the desired end goal. In addition to this, we created a simple and intuitive user interface to help in the adoption phase of the project.
Unlike many strategic modelling attempts, our approach is to model down to an operational level of detail. This involves using machine learning and artificial intelligence methods to model and simulate both the behaviour and change agents in the system. By using a hybridisation of fundamental engineering knowledge and machine learnt insight, our models learn how a system acts (e.g. asset reliability, capacity and performance) and simulates the whole-of-system response to change agents (e.g., policy, projects and the operating environment).
Strategic Energy Transition Tool
At Synengco, we are well equipped to deal with the complex challenges that our customers face. We take a scientific approach that draws from Asset Management standard ISO 55001:2014 and aligns with the US EPA R&D Framework for assessing the impact of policy decisions to navigate towards strategic goals.
This strategic energy transition tool involved the collection and organisation of relevant AEMO datasets, conducting reliability and capacity analysis and visualising results in an easy-to-understand web application. The results helped with executing a systematic approach to identifying risks that could be monitored over time. This could then be used to implement an advanced, data driven, strategic asset management capability to match the Government client’s end goal.
Our client used the app to conveniently explore the results with a clearer, quantitative understanding of an asset portfolio and its respective reliability and capacity. The app could be made to run on near-real-time AEMO data to provide decision-makers with an up-to-date measure of how likely risks are and whether they are trending up or down.