Criteria for the energy management systems
| Criteria . | Description . | Author(s) . |
|---|---|---|
| Real-time monitoring | Data on energy consumption must be provided by the system at various temporal intervals (for instance every 15 minutes, every hour, every day and every week). This enables the end-users to relate near real-time data with their energy usage behaviors | Arboleya et al. (2015); Zhou et al. (2016) |
| Disaggregation of data | Providing disaggregated data for various appliances can assist energy consumers who frequently have misconceptions about the amount of energy used by specific appliances. Information about the effects of turning on or off a specific appliance in real-time can be very helpful to consumers. The provision of disaggregated data also accentuates the effects of long-term adjustments, such as switching to an energy-efficient appliance. Numerous EM systems employ indirect load sensing techniques to deliver disaggregated data based on unique current and voltage waveform “signatures” of individual appliances | Aman et al. (2013) |
| Availability and accessibility | The system must provide the consumer with constant access to the information via an intuitive interface, whether it be a physical device or a web or mobile portal that also allows remote access to the data. EM systems may also employ push technology to deliver urgent notifications to users’ mobile devices or computer screens | Elzabadani et al. (2005); Sekhar et al. (2022) |
| Data integration | In addition to current energy usage, EM systems must incorporate additional types of data, including ambient temperature, humidity, acoustics and light, as well as consumer historical data, usage information for various appliances and peer consumption information | Majdi et al. (2022) |
| Affordability | It should be simple to configure and maintain. It ought to be inexpensive to operate and use little energy. These elements facilitate widespread adoption by lowering the entry barrier to the system | Shah et al. (2013; Zhou et al. (2016) |
| Control | Devices should be under the system’s control remotely, automatically and according to programming. In general, the consumer must carry out necessary control operations manually. However, automatic actions or a digital control option are more efficient | Beaudin and Zareipour (2015); Kusakana (2017); Zhou et al. (2016) |
| Cyber security and privacy | Security issues arise when EM systems transmit data and control signals. The disclosure of consumer personal consumption profiles raises privacy concerns as well. The system must authenticate all transactions to guarantee the security of user data and control functions and prevent unauthorized access by third parties | Sayed and Gabbar (2018) |
| Data intelligence and analytics | The intelligence component is a desirable trait in modern EM systems. In addition to having little time, consumers frequently lack a thorough understanding of electrical systems. The system should take intelligent actions to balance energy consumption and consumer comfort. For this, it may be necessary to use methods from machine learning, human-computer interaction and big data analytics to identify usage patterns and suggest possible courses of action. By doing this, consumers are relieved of the constant burden of directly operating and controlling every appliance | Aman et al. (2013) |
| Criteria . | Description . | Author(s) . |
|---|---|---|
| Real-time monitoring | Data on energy consumption must be provided by the system at various temporal intervals (for instance every 15 minutes, every hour, every day and every week). This enables the end-users to relate near real-time data with their energy usage behaviors | Arboleya et al. (2015); Zhou et al. (2016) |
| Disaggregation of data | Providing disaggregated data for various appliances can assist energy consumers who frequently have misconceptions about the amount of energy used by specific appliances. Information about the effects of turning on or off a specific appliance in real-time can be very helpful to consumers. The provision of disaggregated data also accentuates the effects of long-term adjustments, such as switching to an energy-efficient appliance. Numerous EM systems employ indirect load sensing techniques to deliver disaggregated data based on unique current and voltage waveform “signatures” of individual appliances | Aman et al. (2013) |
| Availability and accessibility | The system must provide the consumer with constant access to the information via an intuitive interface, whether it be a physical device or a web or mobile portal that also allows remote access to the data. EM systems may also employ push technology to deliver urgent notifications to users’ mobile devices or computer screens | Elzabadani et al. (2005); Sekhar et al. (2022) |
| Data integration | In addition to current energy usage, EM systems must incorporate additional types of data, including ambient temperature, humidity, acoustics and light, as well as consumer historical data, usage information for various appliances and peer consumption information | Majdi et al. (2022) |
| Affordability | It should be simple to configure and maintain. It ought to be inexpensive to operate and use little energy. These elements facilitate widespread adoption by lowering the entry barrier to the system | Shah et al. (2013; Zhou et al. (2016) |
| Control | Devices should be under the system’s control remotely, automatically and according to programming. In general, the consumer must carry out necessary control operations manually. However, automatic actions or a digital control option are more efficient | Beaudin and Zareipour (2015); Kusakana (2017); Zhou et al. (2016) |
| Cyber security and privacy | Security issues arise when EM systems transmit data and control signals. The disclosure of consumer personal consumption profiles raises privacy concerns as well. The system must authenticate all transactions to guarantee the security of user data and control functions and prevent unauthorized access by third parties | Sayed and Gabbar (2018) |
| Data intelligence and analytics | The intelligence component is a desirable trait in modern EM systems. In addition to having little time, consumers frequently lack a thorough understanding of electrical systems. The system should take intelligent actions to balance energy consumption and consumer comfort. For this, it may be necessary to use methods from machine learning, human-computer interaction and big data analytics to identify usage patterns and suggest possible courses of action. By doing this, consumers are relieved of the constant burden of directly operating and controlling every appliance | Aman et al. (2013) |