Analysis Comparing Energy Efficiency Degrees
In the small northern European country of Estonia, a sample household has embraced the future of energy management. By adopting multi-asset and multi-market optimization strategies, this household is reaping significant annual electricity cost savings.
The household's electric vehicle (EV), with a consumption of 20 kWh/100 km, is connected to a 7.4 kW charger. It is charged between 18:00 and 08:00 on weekdays and between 15:00 and 10:00 on weekends. The EV allows bidirectional charging, which plays a crucial role in the optimization strategy.
The household's solar energy solution, with a maximum production capacity of 7.5 kW, produces a total annual production of 6981 kWh. This renewable energy source is integrated into the optimization system, which handles multi-asset and multi-market optimization.
The optimization system, powered by an energy optimizer, leverages real-time data, predictive algorithms, and multi-resource coordination. It responds dynamically to electricity price signals, avoiding costly peak usage charges and maximizing cost efficiency.
If the charging of the electric car was optimized according to market prices, the household could save approximately 400€ per year. In a fully optimized household, the EV is often fully charged in the early morning hours and sends electricity to the grid during hours with high electricity prices. This bidirectional flow of energy not only reduces the household's energy costs but also contributes to grid stability.
The optimization of multiple assets (EV and home battery) can make the electricity cost negative. The household, with a Huawei Luna2000-10-S0 home battery, could achieve a total annual cost of -€191. This means that the household not only saves on its electricity bill but also earns money by supplying excess energy back to the grid.
The network package of the household is Network 4, and the electricity package is variable, based on stock market prices. The household consumes 9654 kWh of electricity per year and has a main fuse of 20 Amps.
In addition to the direct cost savings, the optimization system also decides to zero the total consumption of the household during hours with small price arbitrage opportunities. This strategy further reduces the household's energy costs.
The Baltic frequency markets are still in the test phase, but the potential for further cost savings is significant. The full potential of energy optimization could potentially achieve the net-negative energy cost.
In conclusion, the multi-asset and multi-market optimization of household energy use can significantly reduce annual electricity costs by coordinating diverse energy resources and leveraging multiple energy markets or programs. By adopting these strategies, households can realize annual electricity cost savings typically ranging from 10% to over 15%. The added benefits include utility incentives and improved grid integration.
- The household's electric vehicle (electric-vehicles) and home battery (multiple assets) optimized for market prices could potentially result in a negative annual electricity cost (-€191).
- The renewable energy source (renewable-energy) from the household's solar energy solution (solar energy solution) is integrated into the optimization system, contributing to the household's reduction in energy costs.
- With the multi-asset and multi-market optimization strategies (multi-asset and multi-market optimization) applied to the household's lifestyle (lifestyle, which includes the usage of electric vehicles and renewable energy), significant annual electricity cost savings (typically ranging from 10% to over 15%) can be realized.
