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Decentralisation of energy generation and distribution to local districts or microgrids is viewed as an important strategy to increase energy efficiency, incorporate more small-scale renewable sources and reduce greenhouse gas emissions. To achieve these goals, an intelligent, context-aware, adaptive energy management platform is required. This paper will demonstrate two district energy management optimisation strategies; one that optimises district heat generation from a multi-vector energy centre and a second that directly controls building demand via the heating set point temperature in addition to the heat generation. Several Artificial Neural Networks are used to predict variables such as building demand, solar photovoltaic generation, and indoor temperature. These predictions are utilised within a Genetic Algorithm to determine the optimal operating schedules of the heat generation equipment, thermal storage, and the heating set point temperature. Optimising the generation of heat for the district led to a 44.88% increase in profit compared to a rule-based, priority order baseline strategy. An additional 8.04% increase in profit was achieved when the optimisation could also directly control a proportion of building demand. These results demonstrates the potential gain when energy can be managed in a more holistic manner considering multiple energy vectors as well as both supply and demand.

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy consumption and associated greenhouse gas emissions from buildings has acted as a catalyst in the increasing installation of meters and sensors for monitoring energy use and indoor environmental conditions in buildings. This paper reviews the state-of-the-art in building energy metering and environmental monitoring, including their social, economic, environmental and legislative drivers. The integration of meters and sensors with existing building energy management systems (BEMS) is critically appraised, especially with regard to communication technologies and protocols such as ModBus, M-Bus, Ethernet, Cellular, ZigBee, WiFi and BACnet. Findings suggest that energy metering is covered in existing policies and regulations in only a handful of countries. Most of the legislations and policies on energy metering in Europe are in response to the Energy Performance of Buildings Directive (EPBD), 2002/91/EC. However, recent developments in policy are pointing towards more stringent metering requirements in future, moving away from voluntary to mandatory compliance. With regards to metering equipment, significant developments have been made in the recent past on miniaturisation, accuracy, robustness, data storage, ability to connect using multiple communication protocols, and the integration with BEMS and the Cloud – resulting in a range of available solutions, selection of which can be challenging. Developments in communication technologies, in particular in low-power wireless such as ZigBee and Bluetooth LE (BLE), are enabling cost-effective machine to machine (M2M) and internet of things (IoT) implementation of sensor networks. Privacy and data protection, however, remain a concern for data aggregators and end-users. The standardization of network protocols and device functionalities remains an active area of research and development, especially due to the prevalence of many protocols in the BEMS industry. Available solutions often lack interoperability between hardware and software systems, resulting in vendor lock-in. The paper provides a comprehensive understanding of available technologies for energy metering and environmental monitoring; their drivers, advantages and limitations; factors affecting their selection and future directions of research and development – for use a reference, as well as for generating further interest in this expanding research area.