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The Royal Institute of Technology is the Sweden's first polytechnic and it accounts for one-third of Sweden’s technical research and engineering education capacity at university level.

Expertise summary

The research activities of the Automatic Control Lab, Royal Institute of Technology (KTH), are focused on modeling, identification, and control of industrial systems as well as applications in systems biology, communication and autonomous systems.

Virtual Micro Grid Laboratory

Within the EIT ICT Labs SES, and motivated by ongoing smart grid pilot research within the Stockholm Royal Seaport project, partners from industry and academia have combined resources to develop a virtual laboratory for testing ICT infrastructures within the micro-grid. Distributed across multiple academic and industrial research labs, this Virtual Micro Grid Laboratory (VMGL) provides unprecedented capabilities of evaluating ICT infrastructures for performing energy management related services, such as distribution automation, demand response, and micro-grid control. Within the virtual lab, KTH contributes to the Information Management component by developing a demand-side scheduling algorithm and the smart home EMS, which is responsible for locally scheduling end-user smart appliances at the residential level, based on end-user preferences, prior contractual agreements, electric pricing and CO2 emission figures. Moreover, together with Ericsson, has performed an evaluation of Long-Term Evolution (LTE) as a ICT infrastructure for micro-grids. Further details on the VMGL can be found in File:ISGT2012 final.pdf. Further details on the specific requirements imposed by a smart grids on the LTE communication infrastructure and on the latency offered by the LTE network to smart grids components are presented in File:REAL-TIME SCHEDULING IN LTE FOR SMART GRIDS.pdf. In this work, an empirical mathematical model of the distribution of the latency is also established.

Smart Homes

  • Control of temperature, air quality, individual electrical appliances, air quality and light using wireless sensors network through PLC.

Electricity consumption varies between different hours of the day, between days of the week, and between seasons of the year, where the highest power demand typically occurs when the outdoor temperature drops. Environmental and economical reasons will, in the near future, require distribution companies to consider more complex power balance scenarios based on the introduction of large scale renewable electricity generation, personal electrical vehicles (PEVs) and distributed electricity generation in residential areas.Load balancing of urban electrical loads, such as residential/ industrial electricity consumption, can be accomplished by minimizing the usage of non-renewable generation and scheduling controllable loads to times when renewable energy generation is high. Particular ways to engage the consumers in participating in load balancing is achieved through economic incentives such as time-varying electricity tariff (e.g. spot pricing), or CO2 footprint for environmentally concerned consumers (e.g. the Stockholm Royal Seaport project, [[1]]).Studies have demonstrated the value of time-varying electricity tariff in the management of the power grid, especially in the reduction of peak power consumption; however, such load balancing is feasible only if the consumers are both able and willing to consider tariff information. Hence, an automatic decision support system is highly desirable, that either directly takes control of the appliance operation or provides simple advice to the consumers. KTH proposed a smart appliance scheduling framework, capturing all relevant appliance operations. Further details on that can be found in File:Scheduling Smart Home Appliances Using MILP.pdf

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