UEEFS2008 — Explore data and automation in smart energy systems

Elements & performance criteria

Performance evidence

• interpret a project brief to identify the requirements of a basic automation solution for a real-world energy-related problem in a familiar setting
• plan a basic ELV automation solution that uses sensors or input devices to trigger a controlled output
• create a visual representation of the proposed solution using labelled diagrams or digital simulations to demonstrate how the system works
• select ELV components, tools, and materials required for the proposed solution and check for correct function and safe condition
• apply safety procedures, including shut-down and isolation procedures before working on the system
• assemble the ELV d.c. automation solution using sensors, input devices, and output components
• operate the ELV d.c. solution to show how data is collected, interpreted, and used to trigger a controlled response
• test the solution to identify basic faults or performance issues
• make a basic adjustment to improve solution performance
• record actions and results clearly using written notes, labelled diagrams or digital tools
• communicate information about the automation solution while participating in project activities with others, using appropriate energy sector terminology to describe the task outcomes and the benefits of the proposed automation solution.

Knowledge evidence

• entry-level occupations, emerging roles and career pathways in the energy sector related to data, automation and telecommunications work
• the effect of smart energy systems on electrical roles in the energy sector, including requirements for electricians and technicians to configure and install: o smart meters, home energy management systems, and connected devices o solar systems with smart inverters and remote monitoring tools for residential and commercial applications o heating, ventilation, air conditioning and refrigeration (HVACR) systems that use building automation technologies, sensors and data to optimise climate control and energy use
• how data is used to support automation and improve energy efficiency in smart energy systems, including: o types of data used in smart energy systems, including temperature, light, motion, and energy usage data o how data is generated using sensors and digital devices o how data is accessed or collected using basic interfaces or monitoring tools o how data is used to make decisions or trigger automated actions, such as switching devices on or off based on conditions o how automation based on data can help reduce unnecessary energy use and improve efficiency in everyday environments
• benefits of typical smart energy technologies used in homes, schools or workplaces, including: o reducing energy waste by automatically turning devices off when not needed o improving comfort and convenience by adjusting lighting, temperature or appliances based on user needs or environmental conditions o lowering energy costs through more efficient use of electricity and better monitoring of energy consumption o enabling remote monitoring and control of energy systems through mobile apps or connected devices o supporting environmental sustainability by reducing unnecessary energy use and integrating with renewable energy systems o increasing safety through automated alerts, sensor-based lighting, or smart shutdown features in the event of abnormal conditions
• the purpose and function of components used in telecommunications, data, and automation systems relating to energy sector work, including: o traditional telecommunications cabling systems in networked environments o key elements in a basic automated smart energy process o sensors, controllers, actuators, and data inputs and output devices
• safety principles when working with ELV components and digital tools related to course project work, including data security and privacy considerations when using connected systems
• basic numerical concepts relevant to data and automation systems, including interpreting sensor readings, comparing on/off thresholds, and tracking changes in data values over time
• faults or problems that might affect ELV data and automation demonstrations or models, including incorrect sensor placement, loose connections, or inaccurate data inputs, and simple adjustments to improve performance.

Foundation skills

• cognitive skills: access and interpret information about how data and automation are used in smart energy systems; interpret a project brief; identify opportunities to apply data and automation technologies in familiar energy-related settings
• technical and procedural skills: plan and represent a basic automation solution; select and check a limited range of tools, components, and materials; apply safety procedures; assemble, operate and test an ELV direct current (d.c.) automation system; make basic adjustments; record project actions and results; use digital tools where required to record, organise, compare, or present project information
• communication skills: communicate information about an automation solution and its benefits; use appropriate energy sector terminology effectively
• collaboration skills: participate in project activities with others.

Unit content sourced from training.gov.au — © Commonwealth of Australia, licensed under CC BY 4.0. Auditori is not affiliated with the Department of Employment and Workplace Relations.

Questions about assessing UEEFS2008