The project aims to make recommendations about the implementation of control, communications, and business schemes for enabling thermal loads to provide ancillary services in the form of control reserves for the Swiss power grid. Ancillary services provide a fast-reacting compensation for a power shortage or surplus in the transmission grid.

Thermal loads such as building HVAC systems and household appliances have an inherent thermal storage capacity, which provides flexibility in their power consumption without compromising their original purpose. Hence, one can envision effective demand response schemes exploiting these thermal loads to balance the power grid locally, reducing transmission congestions, improving ancillary service market operations, and reducing power peaks. Most importantly, this facilitates the integration of renewable energy sources, which critically rely on ancillary services today. Heatreserves is the first external project that used the ehub platform after its launch.

Partners: nanoterra
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In Switzerland and many other European countries, the future energy system will heavily rely on renewable energy. This will cause an important reengineering of this part of the electrical infrastructure. Therefore, a massive penetration of distributed power sources and distributed storage devices calls for a new layout and system design of the urban energy system.

The results of our studies will form the basis for the planning such systems and grids. Both the design (planning) of the energy system and the operation will be considered.

The developed microgrid framework consists of independent resource and grid agents communicating with each other. The goal is that the grid operates in a safe state as it can determine the load on its lines and the resources can operate flexibly and independently. This cooperation-based, distributed control scheme has a cycle time of 100ms, leading to fast corrections form optimal trajectories. With this scheme one can also operate in islanding mode with the ability to connect and disconnect whole districts to the distribution grid.

Partner: CCEM
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Decentral batteries or district sized battery installations provide a layer of flexibility to the distribution grid and its stakeholder. In SALISC Empa investigates in the design and operational stages of battery usages to determine their profitability in 2018 and in 2025. Multiple storage technologies, sizes, locations and control schemes are analyzed according the general conditions of a distribution grid of Glattwerke AG acting as DCO. The most promising solutions are implemented on the ehub platform and its storage technologies to exemplary validate the performance of the found solutions. 

Especially the effect of Molten Salt (NaNiCl₂) and Lithium Ion (NMC-G) Storages is investigated. The impact of additional of Super Capacitors should highlight the significance of this technology to a storage setup in a distribution grid.

Together with Empa, TwingTec develops the next generation of wind energy using a tethered drone that flies like a kite. During this project, a full scale tethered drone prototype will be developed and tested.

The goal of this project is to design, build and test a full scale tethered drone prototype for a 10kW pilot system. This prototype will address the two critical remaining challenges before the development of an upscaled system can begin: efficiency and energy autonomy.

Funding body: Innosuisse
Partner: TwingTec AG
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The main goal of the project ECOBATTEM is to experimentally prove that the large installation of battery storage systems (BSS) equipped with an ageing-aware energy management software is the best way to satisfy the 2050 Swiss Energy Strategy. The main reasons behind this goal are:

• The BSS will allow the increase of energy self-consumption and consequently reduce the global CO2 emissions;
• An ageing-aware strategy for BSS deployment allows for a maximized lifetime of the BSS itself with a consequent large renewable energy self-consumption and CO2 reduction;
• A BSS with a minimum state of ageing can be deployed by utility/DSO in order to provide ancillary services to the power grid (such as peak-shaving and frequency/voltage control)

Funding body: BFE
Partners: Aurora’s Grid LLC, Leclanché SA, HES-SO VD, HES-SO Fribourg
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The decentralized control scheme based on Machine Learning (ML) technique proposed in [1] is applied to the NEST microgrid, allocated in the EMPA Laboratory in Dübendorf. However, due to the low voltage magnitudes over the grid, the battery is forced to operate into a high injection regime in order to have consistent results. This increases the local voltages and allows the adoption of the Reactive Power Control (RPC) as active measure to achieve network-wide optimal operation. In this approach, the online optimization problem is performed in two stages. First, a day-ahead optimization problem for the BESS is implemented with the objective to impose high injections during noon hours and guarantee a secure operation. Second, a centralized, OPF-based scheme is used to generate a sequence of optimal DER setpoints accounting for BESS injections. Finally, the local DER controllers are developed as explained in [1] and applied in the real-time operation.

[1] F. Bellizio, S. Karagiannopoulos, P. Aristidou, and G. Hug, "Optimized local control schemes for distribution grids using machine learning techniques," IEEE Power and Energy Society General Meeting, 2018.