• Energy Research

AbstractWorldwide, buildings consume about 40 percent of the overall energy resources and contribute to an average of 30 percent of the global carbon emission. Hence, technologies for improving the energy efficiency of buildings play an essential role in the global fight against climate change. The CELSIUS project aims to improve the energy efficiency and indoor climate of medium to large sized commercial and public buildings by developing an integrated system solution that consists of (1) an IoT-enabled and cloud-based platform for monitoring and diagnostics of building energy performance and indoor climate quality, (2) a middleware software platform for cost-effective large-scale deployment of wireless sensors and gateways, and (3) an IoT network management platform for cost-efficient life-cycle maintenance of sensors and gateways. The integrated system solution will be deployed and demonstrated in a 6000 m2 building in Aarhus, Denmark, and an 18,000 m2 building in Kuala Lumpur, Malaysia. By choosing buildings located in different climate zones on different continents allows the developed system solution to be tested under realistic conditions for the international export market.

Electrical Power Systems should be designed in order to minimize the effects of system disturbances and to enable decision-making based on different configurations and relevant priority analysis. Automatic Under Frequency Load Shedding is a known effective solution to the problem of contingencies in the electrical power grid and it is the last resource to mitigate the damage caused by severe and unexpected contingencies. However, to the best of our knowledge, the load priority configuration, which have been presented so far in load shedding process do not take into account some important aspects, such as social, economic or political importance of the connected loads, as well as how negative is the impact on the public image of power utilities when disconnecting specific load branches. This paper aims to provide a general priority holistic function which can be applied to different load shedding schemes, independent of the adopted philosophy and operating principles. The proposed ranking is developed using a Fuzzy system for load priority classification that takes several aspects into consideration. To illustrate the method, an electrical power system was simulated, comparing a traditional load shedding scheme with two different sets of load priorities and evaluated by the proposed metric.

This paper presents a distributed strategy for the optimal dispatch of islanded microgrids, modeled as unbalanced three-phase electrical distribution systems. To set the dispatch of the distributed generation (DG) units, an optimal generation problem is stated and solved distributively based on primal-dual constrained decomposition and a first-order consensus protocol, where units can communicate only with their neighbors. Thus, convergence is guaranteed under the common convexity assumptions. The islanded microgrid operates with the standard hierarchical control scheme, where two control modes are considered for the DG units: a voltage control mode, with an active droop control loop, and a power control mode, which allows setting the output power in advance. To assess the effectiveness and flexibility of the proposed approach, simulations were performed in a 25-bus unbalanced three-phase microgrid. According to the obtained results, the proposed strategy achieves a lower cost solution when compared with a centralized approach based on a static droop framework, with a considerable reduction on the communication system complexity. Additionally, it corrects the mismatch between generation and consumption even during the execution of the optimization process, responding to changes in the load consumption, renewable generation, and unexpected faults in units.

Within the emerging discipline of Energy Informatics people are researching, developing and applying information and communication technologies, energy engineering and computer science to address energy challenges. In this paper we discuss the challenge of advancing energy informatics to enable assessable improvements of energy performance in buildings. This challenge follows a long-standing goal within the built environment to develop processes that enable predictable outcomes. Implementing this goal in the research framework of energy informatics creates a need for establishing a new underlying assumption, which states that the impact of energy informatics solutions should be assessable. This assumption applies to particular building contexts and when solutions act simultaneously. Research based on this assumption will enable new sound processes for the built environment facilitating informed decision for adding intelligent solutions to buildings compared to only favoring passive building improvements.

Buildings consume up to 42% of the global electricity and the primary emitter of greenhouse gas on the planet. Building efficiency is the largest growing segment in the US, the estimated global revenue by the building efficiency sector is around 210 million dollars, and constantly increases since 2011. Much research already shows the players' passive and conservative attitudes to enter into the energy efficiency market. Especially there are obstacles for the construction companies to redesign their business model from the traditional building business to the smart building market. This paper conducts a qualitative approach with primary and secondary data to investigate the Barriers and opportunities of the construction companies into the smart building market. The result shows the willingness of the players to involve the building efficiency business with huge potential monetary benefits. Meanwhile, the result shows that the barriers can be eased or solved by open collaboration, information and risk sharing, and self-investment, etc. this paper also categorizes nine influential factors with discussions.

Multi-agent systems are well-known for their expressiveness to explore interactions and knowledge representation in complex systems. Multi-agent systems have been applied in the energy domain since the 1990s. As more applications of multi-agent systems in the energy domain for advanced functions, the interoperability raises challenge raises to an increasing requirement for data and information exchange between systems. Therefore, the application of ontology in multi-agent systems needs to be emphasized and a systematic approach for the application needs to be developed. This study aims to investigate literature on the application of ontology in multi-agent systems within the energy domain and map the key concepts underpinning these research areas. A scoping review of the existing literature on ontology for multi-agent systems in the energy domain is conducted. This paper presents an overview of the application of multi-agent systems (MAS) and ontologies in the energy domain with five aspects of the definition of agent and MAS; MAS applied in the energy domain, defined ontologies in the energy domain, MAS design methodology, and architectures, and the application of ontology in the MAS development. Furthermore, this paper provides a recommendation list for the ontology-driven multi-agent system development with the aspects of 1) ontology development process in MAS design, 2) detail design process and realization of ontology-driven MAS development, 3) open standard implementation and adoption, 4) inter-domain MAS development, and 5) agent listing approach.