Is a future conceivable in which all energy devices within a building are networked with each other? A future in which electricity producers and consumers are directly connected to the electricity market? In which electric vehicles are automatically charged at times when plenty of renewable energy is available, whether from your own roof or from the power grid? In which we can pass on our surplus energy directly to our neighbors?
We are sure: This imagined future is in touching distance. As experts in energy management and energy optimization, we at Kiwigrid are making this vision a reality. While we have already realized some scenarios, others are in development. To better understand the networking of energy devices in a complex energy world, we developed a model with five levels for energy optimization.
From manual to autonomous optimization
The five levels of autonomous optimization are based on the five levels of autonomous driving. Each further level requires certain technological developments - thus all levels build on each other. Each level creates new added value for different players in the energy market, including end customers, electricity providers and grid operators. The degree of integration increases with each level until we reach the autonomous optimization at the fifth level.
Level 0: Manual user control
At the base level 0, end customers can view the day-ahead prices from the European power exchange EPEX SPOT and manually adjust their consumption. Users then operate their appliances automatically at times when the exchange price is low.
The app displays the EPEX day-ahead prices and by this motivates end users to adjust their everyday behavior in line with the exchange price. For example, they switch on their washing machine when the exchange price is particularly low.
This level is not yet automated and requires user initiative. Nevertheless, end customers can already save a lot of money through the combination of optimization of private consumption and manual electricity price optimization.**
Level 1: EPEX-automated optimization
At level 1, the energy management system directly integrates the EPEX day-ahead prices. This enables automated control of end customer systems on an EPEX basis. Kiwigrid's energy management system (EMS) recognizes the fluctuating prices and sends automatic control signals to the various controllable consumers.
End customers can activate and configure tariff optimization in the EMS. This means, for example, that the electric vehicle (EV) charges automatically when the market price is particularly low. EPEX-automated optimization can also be combined with solar-optimized charging.
End customers not only save time with the EPEX-automated optimization, but also money. The financial benefit of tariff-optimized charging of the EV is around 185 euros and tariff-optimized operation of the heat pump a further 145 euros per year.**
Level 2: Unidirectional tariff-automated optimization
While the EPEX day-ahead prices serve as the data basis for automated optimization at Level 1, Level 2 automation is based on live tariff data from an electricity supplier. This can also be linked to the exchange price.
The EMS enables end customers' systems to be controlled automatically according to a customer-specific dynamic electricity tariff. End customers can decide on a dynamic tariff directly in the EMS app and conclude a contract immediately.
In combination with variable grid charges, end customers can save almost €1,000 a year with dynamic tariffs: up to €485 when charging their electric car with a tariff-optimized tariff and up to €470 when operating their heat pump with a tariff-optimized tariff. There is great customer acquisition potential for electricity providers if end customers book dynamic electricity tariffs directly in the EMS.**
Level 3: Bidirectional tariff-automated optimization
Level 3 deepens the integration of dynamic tariffs into the EMS through two-way communication with the energy supplier. The EMS now returns live data on generation and consumption as well as forecasts to the energy supplier. This enables the energy supplier to learn which quantities a customer currently needs and how much they will need in the foreseeable future.
Compared to level 2, these are primarily new advantages for energy suppliers and the electricity grid. Energy suppliers can use the additional data to optimize electricity trading and adjust their electricity procurement. Ideally, this will enable energy suppliers to reduce costs.
The energy supplier also has the option of sending price signals to end customers. This allows them to encourage end customers to consume at times when a lot of electricity is available. This actively reduces the load on the electricity grid and prevents overloading. The usual savings potential for end customers is in the same range as for level 2.**
Level 4: Aggregator-automated optimization
At level 4, energy devices can be controlled by the energy supplier. This allows electricity consumption to be adapted directly to live electricity trading. With the explicit permission of the end customer, the energy supplier takes active control of the energy devices. For example, the EV can now charge at the most favorable procurement time.
This creates added value for all parties. End customers receive a flexibility bonus for allowing external control, which is higher than the savings potential of level 3. At the same time, electricity suppliers can minimize their procurement costs as they can actively trade the available flexibility. This also reduces the load on the electricity grid. In addition to the savings achieved up to this point, end customers can benefit from even greater financial advantages thanks to the flexibility bonus.**
Level 5: Local automated optimization
At the final level 5, we integrate the local environment in addition to the building and the energy market. For example, end customers can now also use the surplus electricity from the neighboring photovoltaic (PV) system. The EMS now permanently weighs up the dimensions of the building, energy market and environment against each other. End customers then always obtain their electricity as cheaply and as locally as possible.
Locally automated optimization is based on community and solidarity. In the spirit of the sharing economy, not only homes with PV systems benefit, but also buildings that only have an electricity storage unit, for example.
There are also economic benefits for energy suppliers and grid operators. Energy suppliers can now offer green and locally generated electricity. Grid operators do not have to factor in long transport routes for locally consumed energy and benefit from the grid relief. End customers can generally obtain even cheaper electricity through locally automated optimization than through tariff and aggregator-automated optimization.**
A fully networked energy world
These five levels are not science fiction. At Kiwigrid, we work urgently every day to reach the target level as quickly as possible. One thing is clear: the energy management system is at the heart of a fully networked, autonomous energy world of tomorrow. An EMS is already generating added value for end customers, electricity providers and grid operators, among others, and is also driving the energy transition. Together with the various stakeholders, we ensure that users will always receive the most local, cheapest and greenest electricity in the future.
** The savings were calculated on the basis of real price and consumption data and assumed flexibility potential. Electricity use is shifted to times of low electricity prices.
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