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Smart Energy Application Scenarios

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The energy system will become less and less centralized, consisting of many distributed consumers and producers and therefore distributed energy resources (DER). Due to this decentralization, the communication infrastructure must be adapted, enhanced and deployed in order to receive proper and up-to-date information about the current demand as well as the generation. Based on this data, more precise predictions can be achieved, which help to organize the system of systems in the energy domain. Furthermore, the local energy management systems must be extended with computational power and intelligence to support the decentral organization of the smart grid.

Energy Scenario A: Horizontal Interconnectedness

Virtual power plants (VPP) are an example of horizontal interconnectedness, in which energy generation units of different type and size are interconnected using standardized communication protocols to act like a single big power plant in order to provide a stable and continuous energy. The connected appliances or installations have to meet certain requirements, e.g. conform to the VHPready standard. To balance these kinds of plants, not only generation units, but also storage and consumption entities are required to balance the input and output according to the current demand.
Societal/Human: Users can benefit from connecting the available DER to a central stakeholder as an alternative source of income for the feed-in tariff. VPP operators can use the connected appliances to support the stability of the whole grid, due to control capabilities of each participating entity.
Process: Processes and utilization are optimized based on the operators’ view. Whereas also other optimization strategies are feasible. Information about processes and equipment are transparent to the operator as well as the owner of DER due to billing purposes. Negotiations, management and control between VPP and DER can be partially or fully automated.
Information: Data can be processed in the VPP Backend. Systems will use data also from other sources to predict generation and demand.
Technology: Local energy management systems or gateways.

Energy Scenario B: Vertical Interconnectedness

The vertical interconnectedness in the energy domain can be represented by (local) energy management systems (EMS) which operate, monitor and control, e.g. single buildings or even blocks of buildings – in the field layer different sensor values are collected from several devices and actuators can be controlled. These devices, like simple powermeters or heat pumps are connected to an energy management system as a central controller. Communication protocols and standards like Modbus, KNX, M-Bus, OPC, OBIX as well as proprietary solutions like Apple HomeKit are used in this domain. On top of simple monitoring and control higher value applications and services can be implemented to allow for more accurate predictions, to implement complex rules to support home automation or energy efficiency. These services heavily rely on proper data, adequate models and representations to predict feasible own offerings and demands which are the basis to provide capabilities and services such as load shifting or demand side management.
Societal/Human: Buildings operate autonomously in order to be energy efficient and/or convenient. These buildings can contribute to environmental challenges.
Process: Processes and utilization can be adapted to customer demand and preferences. Energy related services can be offered to external stakeholders. High quality predictions can help to increase the overall efficiency.
Information: Data can be processed in the local EMS or e.g. by using cloud-based solutions for computational intense tasks.
Technology: EMS, Building Management and Control Systems.

Energy Scenario C: Increased Level of Servitisation

The increased level of servitisation can be seen as a result of the digitization process. In the industry and production domain a shift to selling production capabilities or operational times instead of products or machinery can be observed – here terms like “power by the hour” (this is actually a Rolls-Royce registered trademark) or production as a service apply. In this context of the energy domain pay per use models, where the customer only gets charged for the actual consumption, are quite common. Quite new is the factor that appliances or equipment, available at the local sites are used to enable novel services. In this context small, local storage systems can be combined to a so-called swarm battery. The resulting virtual large-scale battery can be used to act as an entity on the energy market or to share energy among participants. In this case technologies supporting communication, remote control and accountability are required to support appropriate billing depending on the contribution of the single appliances.

Energy Scenario D: Specific functionality with limited interconnectedness in a lowly digitized environment

As a fallback to the interconnected services the autonomous operation can be highlighted as an extension to Scenario B. In case the local appliances cannot be connected to external stakeholders the available resources will be used to maintain the required operation locally or with in a limited area. These Micro Grid scenarios can be mapped very well at the neighborhood level. Each building, as a local node in the Micro Grid, offers its services locally in the form of demand response, load shifting, storage capacity, and generation. Due to the local character on the level of e.g. an urban district, this also enables the transfer of further resources such as heat or cooling capabilities. This illustrates the idea of scalability by interconnecting smart energy efficient buildings, which can operate autonomously as a fallback, to a smart micro grid or a smart neighborhood to share and trade available resources.
Aspects on societal/human, processes, information and technologies for scenarios C and D are quite similar to the above scenarios. See above.

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