[Paper Review] Multi-state Operating Reserve Model of Aggregate Thermostatically-Controlled-Loads for Power System Short-Term Reliability Evaluation

Yi Ding, Wenqi Cui+4 more|arXiv (Cornell University)|Feb 1, 2019

Smart Grid Energy Management38 references4 citations

TL;DR

This paper proposes a novel multi-state operating reserve model for aggregate thermostatically-controlled loads (TCLs) to improve short-term power system reliability evaluation. By modeling the dynamic temperature migration within TCLs' hysteresis bands and using cumulants to derive probability distributions of reserve capacity under stochastic conditions, the method enables accurate representation of reserve reliability via LZ-transform, validated through case studies.

ABSTRACT

Thermostatically-controlled-loads (TCLs) have been regarded as a good candidate for maintaining the power system reliability by providing operating reserve. The short-term reliability evaluation of power systems, which is essential for power system operators in decision making to secure the system real time balancing, calls for the accurate modelling of operating reserve provided by TCLs. However, the particular characteristics of TCLs make their dynamic response different from the traditional generating units, resulting in difficulties to accurately represent the reliability of operating reserve provided by TCLs with conventional reliability model. This paper proposes a novel multi-state reliability model of operating reserve provided by TCLs considering their dynamic response during the reserve deployment process. An analytical model for characterizing dynamics of operating reserve provided by TCLs is firstly developed based on the migration of TCLs' room temperature within the temperature hysteresis band. Then, considering the stochastic consumers' behaviour and ambient temperature, the probability distribution functions of reserve capacity provided by TCLs are obtained by cumulants. On this basis, the states of reserve capacity and the corresponding probabilities at each time instant are obtained for representing the reliability of operating reserve provided by TCLs in the LZ-transform approach. Case studies are conducted to validate the proposed technique.

Motivation & Objective

• Address the challenge of accurately modeling operating reserve from thermostatically-controlled loads (TCLs) in short-term power system reliability evaluation.
• Overcome limitations of conventional reliability models that fail to capture TCLs' unique dynamic response during reserve deployment.
• Develop a probabilistic framework to represent the reliability of operating reserve provided by aggregated TCLs under stochastic consumer behavior and ambient temperature variations.
• Enable power system operators to make more informed real-time balancing decisions by quantifying reserve capacity states and their probabilities.

Proposed method

• Formulate an analytical model based on the migration of room temperature within the temperature hysteresis band of TCLs during reserve activation.
• Use cumulants to derive the probability density functions of reserve capacity, accounting for stochastic consumer behavior and ambient temperature fluctuations.
• Apply the LZ-transform approach to compute the state probabilities of reserve capacity at each time instant, enabling multi-state representation.
• Aggregate individual TCL responses into a collective reserve model suitable for system-level reliability assessment.
• Integrate dynamic response characteristics into the reliability model to reflect actual reserve deployment behavior over time.
• Validate the model through case studies under realistic system conditions to demonstrate accuracy and applicability.

Experimental results

Research questions

• RQ1 How can the dynamic response of thermostatically-controlled loads during reserve deployment be accurately modeled for reliability assessment?
• RQ2 What is the impact of stochastic consumer behavior and ambient temperature on the probability distribution of reserve capacity from aggregated TCLs?
• RQ3 How can multi-state reserve capacity representations be derived and applied in short-term power system reliability evaluation?
• RQ4 To what extent does the proposed model improve upon conventional reliability models in capturing TCL-based operating reserve reliability?
• RQ5 Can the LZ-transform approach effectively represent the time-varying states and probabilities of TCL-derived reserve capacity?

Key findings

• The proposed model successfully captures the dynamic temperature migration of TCLs within their hysteresis bands during reserve deployment.
• Cumulant-based derivation enables accurate approximation of the probability density functions of reserve capacity under stochastic conditions.
• The LZ-transform approach effectively computes the time-varying states and probabilities of reserve capacity, enabling multi-state reliability representation.
• Case studies confirm the model's accuracy in representing the reliability of TCL-based operating reserves in short-term system planning.
• The model outperforms conventional approaches by incorporating TCL-specific dynamics, leading to more realistic reserve capacity assessments.
• The framework provides a scalable and analytically tractable method for power system operators to evaluate real-time balancing requirements using TCLs as a reserve resource.