Load Shifting Versus Manual Frequency Restoration Reserve: Evaluating the Financial Incentives for Thermostatically Controlled Loads in Denmark

Core Concepts

Load shifting can be almost as profitable as providing manual frequency restoration reserve (mFRR) services for thermostatically controlled loads in Denmark, although mFRR provision may be more beneficial for power system stability.

Abstract

The paper investigates the financial incentives for thermostatically controlled loads (TCLs), specifically supermarket freezers, to provide demand-side flexibility in two forms: load shifting and manual frequency restoration reserve (mFRR) services.
Key highlights:

A second-order grey-box model is developed to capture the temperature dynamics of a supermarket freezer, which is used to estimate the flexibility potential.
A two-stage stochastic optimization problem is formulated to maximize the flexibility value from the freezer, considering price and activation uncertainties.
An ex-post simulation based on Danish spot and balancing market prices in 2022 shows that load shifting can be almost as profitable as mFRR provision for the TCL.
However, load shifting could lead to larger temperature deviations in the freezer compared to mFRR provision.
The results suggest the need for regulatory measures by the Danish system operator to make the attraction of mFRR provision more obvious for TCLs in comparison to the load shifting alternative.

Stats

The paper uses real data from a supermarket freezer in Denmark, including temperature, valve opening degree, and power consumption measurements.

Quotes

"Load shifting shows to be almost as profitable as mFRR provision, although it could be more consequential for temperature deviations in the freezer."
"This indicates the need for regulatory measures by the Danish system operator to make the attraction of ancillary service provision more obvious for TCLs in comparison to the load shifting alternative."

Key Insights Distilled From

Load Shifting Versus Manual Frequency Reserve: Which One is More Appealing to Flexible Loads?

by Pete... at arxiv.org 04-15-2024

https://arxiv.org/pdf/2309.01987.pdf

Deeper Inquiries

How can the regulatory measures proposed in the paper be designed to effectively incentivize TCLs to provide mFRR services over load shifting?

In order to effectively incentivize Thermostatically Controlled Loads (TCLs) to provide manual Frequency Restoration Reserve (mFRR) services over load shifting, regulatory measures can be designed in the following ways:

Financial Incentives: The regulatory measures can include financial incentives such as higher payment rates for mFRR provision compared to load shifting. By offering a higher financial reward for participating in the mFRR market, TCLs would be more inclined to provide mFRR services.

Market Access: Ensure that TCLs have easy access to the mFRR market and can participate without facing significant barriers. This can be achieved by streamlining the registration and bidding process for TCLs in the mFRR market.

Transparency: Provide transparency in the market mechanisms and pricing structures for mFRR services. TCLs should have a clear understanding of how their participation in the mFRR market can benefit them financially.

Education and Support: Offer educational programs and support to TCLs to help them understand the benefits of providing mFRR services and how to effectively participate in the market. This can include training sessions, workshops, and informational materials.

Flexibility Options: Allow TCLs to have flexibility in their participation, such as offering different contract lengths or flexibility in the amount of reserve capacity they provide. This can cater to the varying needs and capabilities of different TCLs.

By implementing these regulatory measures, TCLs can be effectively incentivized to choose mFRR services over load shifting, thereby contributing to grid stability and reliability.

How can the potential drawbacks or unintended consequences of such regulatory measures be mitigated?

While implementing regulatory measures to incentivize TCLs to provide mFRR services, it is essential to consider potential drawbacks and unintended consequences. Some ways to mitigate these issues include:

Monitoring and Evaluation: Regular monitoring and evaluation of the impact of the regulatory measures can help identify any unintended consequences early on. This allows for timely adjustments to the regulations to address any issues that may arise.

Stakeholder Engagement: Engaging with stakeholders, including TCLs, market operators, and regulatory bodies, can help gather feedback and insights on the effectiveness of the measures. This feedback can inform decision-making and adjustments to the regulations.

Flexibility in Regulations: Building flexibility into the regulatory framework can help accommodate changing market dynamics and unforeseen consequences. This can include provisions for periodic reviews and updates to the regulations based on feedback and market developments.

Risk Management: Implementing risk management strategies to address potential risks associated with the regulatory measures can help mitigate negative impacts. This can include setting up contingency plans and mechanisms to handle any adverse outcomes.

Communication and Transparency: Maintaining open communication and transparency throughout the implementation of the regulatory measures can help build trust and understanding among stakeholders. Clear communication of the objectives, benefits, and potential risks can help mitigate misunderstandings and resistance.

By proactively addressing potential drawbacks and unintended consequences through these mitigation strategies, the regulatory measures can be more effective and successful in incentivizing TCLs to provide mFRR services.

How can the modeling approach be extended to consider a portfolio of heterogeneous TCLs, and what are the implications for the overall flexibility potential and market participation?

To extend the modeling approach to consider a portfolio of heterogeneous Thermostatically Controlled Loads (TCLs), the following steps can be taken:

Modeling Heterogeneity: Develop a modeling framework that can capture the diverse characteristics and behaviors of different types of TCLs within the portfolio. This may involve creating sub-models for different types of TCLs based on their energy consumption patterns, response times, and flexibility potential.

Scenario Generation: Generate scenarios that reflect the variability and diversity within the portfolio of TCLs. This can include scenarios that represent different load profiles, temperature dynamics, and response capabilities of the TCLs in the portfolio.

Optimization Framework: Modify the optimization framework to accommodate the heterogeneity of the TCL portfolio. This may involve introducing additional decision variables, constraints, and objectives to optimize the flexibility provision across the diverse set of TCLs.

Risk Management: Incorporate risk management strategies to address uncertainties and variability within the portfolio. This can include robust optimization techniques, scenario-based analysis, and sensitivity analysis to assess the impact of different scenarios on the overall flexibility potential.

Implications for the overall flexibility potential and market participation include:

Increased Flexibility: A portfolio of heterogeneous TCLs can offer a wider range of flexibility options, allowing for more diverse and tailored responses to grid needs. This can enhance the overall flexibility potential of the system.

Market Participation: By considering a portfolio of TCLs, the market participation of these assets can be optimized to maximize their collective impact on grid stability and reliability. This can lead to more efficient use of TCL flexibility in ancillary service markets.

Diversification: A diverse portfolio of TCLs can help mitigate risks associated with individual assets and provide a more robust and resilient flexibility resource. This diversification can enhance the overall reliability of the grid.
By extending the modeling approach to consider a portfolio of heterogeneous TCLs, the overall flexibility potential and market participation can be optimized to achieve grid stability and efficiency.