As we continue to generate more and more electricity from renewable but intermittent sources, Demand Response (sometimes shortened to “DR”) has emerged as an integral solution for efficiently balancing electricity supply and demand. In this post, we’ll explore how Demand Response works, its benefits, and why a holistic approach is crucial to getting the most out of it.
The Challenge of Balancing Electricity Supply and Demand
Fundamental to any electrical system is the need to balance supply and demand. For decades, countries have done this by generating the right amount of power in real-time, using energy sources that can be dispatched relatively quickly. While some countries like Sweden and Norway have ready access to clean energy sources like hydropower for this purpose, many others need to rely on fossil fuels.
Renewables, for all their benefits, introduce a major problem to the system in the form of intermittency. The sun doesn’t always shine and the wind doesn’t always blow. As renewable generation increases, more and more of our energy is produced hours before or after we need it. The amount of energy we produce and consume may still be balanced, but the timing is off.
Batteries offer a promising solution and technology is evolving quickly, but cost-effective, large-scale storage solutions have yet to hit commercial scale. So what do we do in the short term?
A New Paradigm: Smart Consumption
The good news is that there’s a solution we can take advantage of today. And it boils down to shifting how we consume energy. Or rather, when.
Let’s look at an example of a single EV. If electricity prices are flat, the only factors that determine the vehicle is charging are the habits and schedule of its owner. If they get home around 6:00 pm, guess when the EV will start charging? Just about 6:00 pm.
Now, imagine the energy company has introduced cost-reflective tariffs (e.g. time-of-use rates) or demand charges that penalize consumers exceeding certain kW thresholds. Suddenly the EV owner is subject to price signals, and stands to save on their electricity bill by shifting their charging schedule to when it’s cheap to do so and avoiding demand charges. This “behind-the-meter” optimization is a key feature of Emulate’s software.
As we broaden our perspective to the thousands of EVs and other energy-intensive smart devices in the world, smart consumption has enormous potential to ease the transition to renewable energy and reduce energy costs for consumers and businesses alike. Even better, it can do so without impacting comfort. The trick is to leverage the latent flexibility in our electricity usage. Delaying EV charging until the early hours of the morning is one approach, but several energy-intensive smart devices such as water heaters and HVAC systems can be similarly optimized.
Demand Response: Harnessing Flexibility
Demand Response can take advantage of this untapped flexibility as well. While these programs have typically relied on consumers manually adjusting their thermostat or turning off power-intensive devices, the proliferation of Wi Fi-enabled “smart” devices opens the door for software that can control these assets remotely and make Demand Response programs more effective and cost-efficient.
Current Implementation and Limitations
Stakeholders all along the electricity value chain have recognized the potential of Demand Response and adjusted their strategies accordingly:
- As mentioned above, electricity retailers are progressively exposing end-users to spot prices through different cost-reflective tariffs that incentivize consumption when energy is cheaper.
- Original equipment manufacturers (OEMs) and aggregators are building smart consumption features like smart charging and heating into devices so they can automatically optimize against spot prices.
While these developments have allowed consumers to reduce their electricity bills and accelerate the transition to renewables, they have issues of their own.
For end-users:
- Multiple devices optimizing on the same signals can result in new demand spikes clustered around the cheapest prices, which can overload household fuses.
- These consumption peaks can also result in additional costs if grid companies have introduced demand charges for exceeding a given demand threshold.
- Individual devices tend to optimize against price signals alone, blind to other factors that could determine optimal behavior such as the consumption, generation, and latent flexibility from other devices in the same home system.
For energy companies:
- Just as multiple devices within a single home might create a new demand peak, multiple households might do the same and cause a system-wide peak, causing headaches around distribution network congestion.
- Smart consumption optimizes against electricity prices, which are themselves based on demand forecasts that are inherently uncertain. Shifting demand to a period when output is expected to be high (e.g. a bright, sunny afternoon) only for actual production to underperform can result in significantly higher real costs to the retailer.
A Holistic and Sustainable Approach
To address these challenges, we need a more comprehensive approach. One that:
- Considers multiple signals beyond spot prices. Account for grid tariffs that penalize high power peaks, balancing cheap energy with network load. Non-economic goals like self-sufficiency or minimized CO2 emissions should also be considered.
- Optimizes for the whole home. Devices exist as part of a holistic system, and optimization should treat them accordingly. Incorporate forecasts of each device’s consumption and flexibility, factor in current and predicted solar generation, and account for fuse limits. We analyze the benefits of this approach in greater detail below.
- Takes a system-wide approach. Smart consumption relies on spot prices to optimize usage. These prices attempt to reflect the real cost of energy, but are based on day-ahead forecasts that often prove inaccurate. We need a system that relies less on prediction, and more on reaction. Exposing flexibility to ancillary markets allows device-level consumption to react to system-wide signals that support overall grid stability.
Value Assessment
Emulate has developed a versatile framework to quantify flexibility and the benefits of whole-home optimization. It allows us to incorporate multiple assets – EVs, batteries, solar panels, and various types of HVAC units – and optimize for different objectives like minimizing energy cost, avoiding demand charges, and making a home self-sufficient.
We simulated the electricity usage for a traditional mid-size house in southern Sweden based on different tariff models control strategies:
- Tariff models for consumption
- Hourly tariff, i.e. following spot prices
- Monthly tariff, i.e. based on monthly average of spot prices
- Control strategies
- No smart control, i.e. constant indoor temperature and immediate charging
- Uncoordinated optimization of each device against hourly tariff
- Whole-home optimization that accounts for the cost of energy, demand charges, and income from solar power export
In all simulations, demand charges were applied and excess power from solar panels was sold at a tariff that follows the spot price. When drawing comparisons of savings to a baseline, our reference case is the one with an hourly tariff and without any smart control of appliances. All costs are expressed in SEK. The characteristics of the connected appliances is shown in the table below:
| Source | Max Electrical Power [kW] | Yearly Production / Consumption [kWh] |
|---|---|---|
| EV | 11 | 3,000 |
| Heat pump (with electrical heater) | 2.5 (+4) | 7,000 |
| Base load | 2 | 2,800 |
| Solar panels | 9 | 9,000 |
Our results demonstrate significant gains from smart, coordinated control of these devices:
- With savings ranging from 36% to 65%, whole-home optimization outperforms the uncoordinated control of devices (3% to 40%)
- When spot prices are highly volatile (2022), uncoordinated control manages to maximize the savings at about 40%, but it increases the demand charges compared with the reference case (no smart control and hourly tariff)
- Whole-home optimization is able to minimize the cost of energy by arbitrage while minimizing demand charges. This in turn minimizes the risk of fuse overload and local grid congestion.
- It is worth noting that the whole home optimization with monthly tariffs performs better than uncoordinated spot price optimization with hourly tariff. This is due to the efficient demand charge reduction and also some ability to schedule consumption to maximize profits from solar energy export.
While there are additional benefits of exposing this flexibility to electricity markets and supporting the broader energy system, this requires careful coordination since a device that is participating in the electricity markets cannot be simultaneously optimized for behind-the-meter use. The decision of how to best use any given device will depend on each household’s assets and behavior.
The benefits of a holistic, whole-home approach to optimization are significant and wide-ranging, and Emulate is leading the charge to unlock these benefits to energy companies and consumers today. We are always eager to connect with people excited about this technology, so please reach out to us at hello@emulate.energy!
Conclusion
Demand response represents a promising path forward for efficient and sustainable electricity consumption, but as renewable generation scales up and smart devices become increasingly popular, problems with the traditional approach have been laid bare. Emulate’s software mitigates these issues by accounting for signals beyond spot price, taking a whole-home approach, and seeing the home in the context of the broader electricity market. Every step toward refining and implementing Demand Response strategies brings us closer to a future where clean, affordable energy is accessible for everyone.
Author: Stéphane Velut
