Energy Efficiency Comparison Across Different Optimization Stages
In a modern household located in Estonia, the implementation of multi-directional energy optimization has proven to be a game-changer, leading to significant cost savings.
Equipped with a Huawei Luna2000-10-S0 home battery, solar panels with a maximum production capacity of 7.5 kW, and an electric vehicle with a 20 kWh/100 km electricity consumption, this household is a prime example of how energy optimization can transform the way we consume and produce electricity.
The household's energy consumption amounts to 9654 kWh per year, and with a 20 Amps main fuse, it is connected to the grid through Network 4. The household's electricity package is variable, based on stock market prices, adding an extra layer of complexity to the energy management.
The key to the household's savings lies in the optimization of its energy consumption and production patterns. In the base scenario, with no optimization, the annual electricity cost for the household would be €1830. However, with the addition of bidirectional optimization capability, the household achieves a total annual cost of -€191, meaning the income from the sale of electricity would have been greater than the cost of consumption.
Bidirectional optimization can be performed "naively" or "non-naively". The former optimizes purely according to market prices without considering the baseload of the household or the production of solar panels. The latter, however, takes into account these factors, leading to a more efficient use of energy.
The electric vehicle in the household can perform bidirectional charging, acting as both a consumer and a producer. If the charging of the electric vehicle were optimized according to market prices, the household could save approximately 400€ per year. During hours with high electricity prices, the household sends electricity to the grid (consumption is negative).
In a fully optimized household, the household is virtually disconnected from the grid for many hours and interacts with the grid only when the arbitrage opportunity is high. The full potential of the energy optimization could potentially achieve the net-negative energy cost. The bidirectional charging would have enabled a decrease of €1380 in the energy cost of the household compared to the base scenario.
Examples from utility-scale systems show savings of up to $112,000 annually from optimized battery charging and discharging timed to price fluctuations, highlighting the value of energy storage as part of multi-asset coordination. By shifting accounts to more appropriate rate plans based on actual usage patterns, SMWD saved $375,000 annually without new equipment or operational changes.
These approaches represent a key pathway to affordable, efficient, and sustainable energy use. Potential cost savings for households leveraging multi-directional energy optimization with simultaneous control of multiple assets across various energy markets can range from hundreds to several thousands of dollars annually, driven by tariff optimization, peak shaving, participation in demand response, and leveraging incentives and automated controls.
References:
[1] Energy Storage News. (2021). Utility-scale energy storage projects save $112,000 a year with optimized battery charging and discharging. [online] Available at: https://www.energystoragenn.com/news/utility-scale-energy-storage-projects-save-112000-a-year-with-optimized-battery-charging-and-discharging
[2] Greentech Media. (2020). How AI is Changing Energy Management. [online] Available at: https://www.greentechmedia.com/articles/how-ai-is-changing-energy-management
[3] Smart Energy International. (2021). Aggregated control of distributed energy resources yields $33 million in rebates and incentives. [online] Available at: https://www.smart-energy-international.com/articles/2021/08/aggregated-control-of-distributed-energy-resources-yields-33-million-in-rebates-and-incentives
- Renewable energy, such as solar panels, plays a significant role in the household's energy optimization strategy, contributing to cost savings and potential net-negative energy cost.
- The finance sector can benefit from the implementation of multi-directional energy optimization due to potential cost savings of up to $112,000 annually from optimized battery charging and discharging timed to price fluctuations in utility-scale systems.
- By leveraging multi-directional energy optimization with simultaneous control of multiple assets, households can achieve annual cost savings ranging from hundreds to several thousands of dollars, driven by tariff optimization, peak shaving, participation in demand response, and incentives. This aligns with a sustainable lifestyle, enabling affordable and efficient energy use.
