Structuring data to capture energy reticulation knowledge
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Energy management is essential due to the increase in energy costs and its effects on the environmental footprint of an industrial site. Managing energy is an essential but complicated task. This complexity derives itself from the interactions between industrial processes, large energy reticulation networks and a broad scope of work. Energy reticulation is the network of energy streams that flow through an industrial site. The continuous measurement of energy streams generates data, which quantifies and captures information. This quantified view of the energy reticulation informs the energy manager’s decisions. The value-based information needs an additional understanding of the energy reticulation to generate useful knowledge. A framework that defines and organises each measurement can address this need. Defining and organising data through a data structure improves access to relevant data. The current use of primitive spreadsheets or rigid data structures limits access to the relevant data in an organisation. There is thus a need for a simple solution to improve data access, which does not require specialists. Relevant data will address energy management questions. An adjustable structure is required to provide access to knowledge captured in data because relevance fluctuating attribute. The energy manager must also be able to define data continuously. Energy and knowledge management thus has to guide the development of the framework. An adjustable data-structuring framework was developed using metadata to make data accessible. Metadata is additional data consisting of terms that describe the value-based data. The use of the developed data structure allows continuous energy audits to be performed. The data structure was made interactive and dynamic through information technology. The required quantified view of the industrial process’ energy reticulation was achieved. The data-structuring framework was used to aid energy managers with the energy management scope. A mining case study was used to verify and validate the data structure’s ability to enable energy management. The data structure was built for a complicated compressed air ring. The improved data access led to energy-saving observations worth R 2.6 million. Continuously defining and organising data improves access to relevant energy management data. The framework was verified and validated using a mining case study. Energy management is enabled by improved access to relevant data.
- Engineering