Population Of Thermostatically Controlled Loads Research Articles

A unified state space model for aggregation and coordination of large-scale TCLs and EVs for frequency regulation

A unified state space model for aggregation and coordination of large-scale TCLs and EVs for frequency regulation

Distributed Control of Clustered Populations of Thermostatic Loads in Multi-Area Systems: A Mean Field Game Approach

Thermostatically controlled loads (TCLs) can effectively support network operation through their intrinsic flexibility and play a pivotal role in delivering cost effective decarbonization. This paper proposes a scalable distributed solution for the operation of large populations of TCLs providing frequency response and performing energy arbitrage. Each TCL is described as a price-responsive rational agent that participates in an integrated energy/frequency response market and schedules its operation in order to minimize its energy costs and maximize the revenues from frequency response provision. A mean field game formulation is used to implement a compact description of the interactions between typical power system characteristics and TCLs flexibility properties. In order to accommodate the heterogeneity of the thermostatic loads into the mean field equations, the whole population of TCLs is clustered into smaller subsets of devices with similar properties, using k-means clustering techniques. This framework is applied to a multi-area power system to study the impact of network congestions and of spatial variation of flexible resources in grids with large penetration of renewable generation sources. Numerical simulations on relevant case studies allow to explicitly quantify the effect of these factors on the value of TCLs flexibility and on the overall efficiency of the power system.

Aggregation and Optimal Management of TCLs for Frequency and Voltage Control of a Microgrid

A novel hierarchical Energy Management System (EMS) framework is proposed for the incorporation of Thermostatically Controlled Loads (TCLs) in the provision of ancillary services, namely frequency and voltage control of a microgrid. The TCL population is aggregated as a function of the ambient temperature, voltage and frequency using a neural network-based approach. The proposed EMS comprises primary and secondary control levels. TCLs' participation in the primary control is selected to be semi-autonomous in order to obtain a fast response with low communication burden. The secondary control is centralized and aims to find the optimal dispatch of regulating resources including TCL clusters in order to minimize frequency and voltage deviations as well as grid operation cost. The secondary control relies on a Trust-Region Power Flow (PF)-based multi-objective optimization. Simulation results demonstrate that the participation of TCLs in the proposed EMS does not compromise customer comfort while short cycling and the number of switching events are minimized.

Robust Hierarchical Control Mechanism for Aggregated Thermostatically Controlled Loads

Thermostatically controlled loads (TCLs) are good candidates for direct load control (DLC). They can be aggregated to join the electricity market through a centralized management performed by virtual power plant (VPP). However, there are two main concerns that arise when TCLs participate in DLC. The first is related to the dispatchability of VPP against normal energy demand of individual TCLs in uncertain time-variant environments. The second refers to the tremendous increase of communication and computational requirements needed to perform DLC on a large population of TCLs. This paper introduces aggregators between the DLC controller and TCLs with a novel robust control mechanism to reconcile these concerns. The control mechanism is implemented with two layers: the upper layer suppresses the control payback effect with a quadratic optimization model, and the lower layer addresses the power trajectory tracking with a novel payback tracking error model (PTEM). The control method needs minimum sensing infrastructure since it requires power data only at the aggregation level. Our simulations resulted in a robust reference power tracking by the aggregator with a percentage root mean squared error between 3.33% – 5.69% under uncertain time-variant environments. The continuous responsiveness indicates that the aggregators manage to convert the aggregated TCLs into “manageable resources” that ensure the dispatchability of VPP.

Quantifying flexibility of load aggregations: impact of communication constraints on reserve capacity

Due to the increased use of variable renewable energy sources, more capacity for reserves is required. Non-generating resources such as thermostatically controlled loads (TCLs) can arbitrage energy prices and provide reserves due to their thermal energy storage capacity. The quantity of reserves depends not only on the aggregate power capacity, but also on information and communication technology, exogenous parameters, and system operator requirements. Specifically, the practical limitations origin from (i) communication constraints, (ii) ambient temperature, and (iii) the dispatch time of the activation signal. This study explores the impact of these parameters on the amount of reserves that an aggregator of TCLs can provide to the system operator based on centralised control of a TCL population. A decision support tool is proposed that can be used by aggregators to decide on maximum dispatchable reserve bids. The method can accommodate the specific control algorithm and TCL population of an aggregator and is based on offline computation. It constitutes a powerful reserve bid library to be used when optimisation tools become computationally intractable due to the increased number of decentralised flexible loads.

Aggregate Power Control of Heterogeneous TCL Populations Governed by Fokker–Planck Equations

This paper addresses the modeling and control of heterogeneous populations of thermostatically controlled loads (TCLs) operated by model predictive control (MPC) schemes at level of each TCL. It is shown that the dynamics of such TCLs populations can be described by a pair of Fokker-Planck equations coupled via the actions in the domain. The technique of input-output feedback linearization is used in the design of aggregate power control, which leads to a nonlinear system in closed loop. Well-posedness analysis is carried out to validate the developed control scheme. The closed-loop stability of the system is assessed by a rigorous analysis. A simulation study is contacted, and the obtained results confirm the validity and the effectiveness of the proposed approach.

A Packetized Energy Management Macromodel With Quality of Service Guarantees for Demand-Side Resources

Using distributed energy resources (DERs), such as thermostatically controlled loads (TCLs), electric vehicles (EVs), and energy storage systems (ESSs) as a way to manage demand has been known for decades. A demand management scheme that explicitly considers the individual DER's local quality of service (QoS) is known as demand dispatch. Packetized energy management (PEM) is a demand dispatch paradigm that borrows packet-based concepts from wireless communications to dynamically manage fleets of DER at-scale and in realtime via small, discrete fixed-duration/fixed-power energy packets. PEM addresses QoS in a bottom-up fashion by having a coordinator authorize/deny incoming requests from DERs to consume energy packets. This manuscript extends prior work on modeling a large-scale population (i.e., macro-model) of homogeneous TCLs and ESSs operating under the PEM paradigm. In particular, we extend the macro-model methodology to include deferrable loads (DLs), such as EVs, together with analysis of QoS guarantees. Comparisons between an agent-based (micro-model) simulation and the proposed macro-model are presented to validate modeling accuracy and QoS guarantees.

Demand response based desynchronization of thermostatically controlled loads with hardware implementation

Smart buildings are the need of the day with increasing demand-supply ratios and considerable deficiency to generate them. In any modern nonindustrial infrastructure, these demands mainly comprise thermostatically controlled loads (TCLs), which can be maneuvered. TCLs, such as air-conditioners, heaters, and refrigerators, are ubiquitous and their operating times can be controlled to achieve desired aggregate power. This power aggregation, in turn, helps achieve load management targets and thereby serves as an ancillary service (AS) to the power grid. In this work, a distributed averaging protocol is used to achieve the desired power aggregate set by the utility using steady-state desynchronization. The results are verified using a computer program for a homogeneous and heterogeneous population of TCLs. Furthermore, a load following scenario has been implemented using the utility as a reference. Apart from providing a significant AS to the power grid, the proposed idea also helps reduce the amplitude of power system oscillations imparted by the TCLs. Hardware-based results are obtained to verify its implementation feasibility in real-time.

State Space Modeling and Control of Aggregated TCLs for Regulation Services in Power Grids

Thermostatically controlled loads (TCLs), which possess thermal inertia, have attracted additional attention for providing ancillary services to power systems. In this regard, the aggregation model for TCLs is critical for evaluating the performance and optimizing the control of a population of TCLs. We learn by theoretical analyses and simulations that the accuracy of the state space model in most cases is deteriorated by applying longer TCL dispatch periods. Thus, a modified aggregated TCL model is proposed and a new state transition matrix is derived in this paper to improve the TCL modeling accuracy for the provision of grid regulation services. The proposed control model for the aggregated TCL accounts for compressor time delays that would enhance the collective TCL behavior. A probabilistic control strategy is presented to reduce the adverse impacts on the durability of TCL compressors and communication requirements for implementing the TCL control signal. Simulation results demonstrate that the proposed aggregated TCL model with control signals can closely follow actual TCL behavior and the proposed control strategy can reduce the number of TCL switching for providing ancillary services to power systems.

Impact of Uncertain Parameters on TCL Power Capacity Calculation via HDMR for Generating Power Pulses

Thermostatically controlled loads (TCLs) have attracted additional in power system operations, is mostly because of their flexibility in supplying demand response (DR). So, it is vital to identify accurate parameters for aggregated TCL populations, which is often a cumbersome task in practical applications due to inaccurate power metering, end-users’ random behavior for consuming energy in real-time, and privacy issues pertaining to the availability and the collection of individuals’ data. This paper investigates the TCL power capacity calculation strategy and the impact of uncertain parameters on TCL power capacity for generating power pulses. First, a TCL power capacity calculation strategy which links on–off switching states with temperature set-point adjustments is proposed to remove TCLs that are deemed unsuitable for DR dispatch as they satisfy end-users’ comfort needs. Second, high dimensional model representative (HDMR) is applied to identify important parameters for quantifying the impact of uncertain heterogeneous parameters on TCL power capacities. In addition, a fast framework is provided for reducing the computation burdens in capacity calculation. Simulation results demonstrate that: 1) proposed TCL power capacity calculation strategy can maintain end-users in respective comfort ranges; 2) important parameters can be effectively identified by HDMR; and 3) TCL power capacity can be calculated quickly via HDMR in various dispatch periods.

Dynamic dispatch of thermostatically controlled loads using phase oscillator model

Dynamic dispatch of thermostatically controlled loads using phase oscillator model

Multi-Time-Scale Modeling and Parameter Estimation of TCLs for Smoothing Out Wind Power Generation Variability

Thermostatically controlled loads (TCLs) have demonstrated their potentials in demand response. One of the key challenges for TCLs to be integrated into the system-level operation is building a compact aggregated model, in which the TCL primary behaviors are accurately captured. In this paper, TCLs are aggregated as a virtual generator and two batteries according to their different compressor types and control methods for smoothing out multi-time-scale variability of wind power generation. This will bring system operator great convenience to manage TCLs and conventional components when the system-level decisions are made. Accordingly, accurate parameters of virtual generator and batteries are critical to effectively coordinate TCLs with other resources in the system operation. However, it tends to be difficult to obtain such aggregated parameters as a result of insufficient data for each TCL. To address this problem, high-dimensional model representation (HDMR) is introduced to estimate the aggregated parameters of virtual generator and batteries using the probability distribution of TCL parameters. A numerical simulation study demonstrates that aggregated parameters of virtual generator and batteries can be accurately estimated by HDMR. And virtual generator and batteries are able to follow actual behaviors of TCL populations in power system operations.

A Dynamical Systems Approach to Modeling and Analysis of Transactive Energy Coordination

Under transactive (market-based) coordination, a population of distributed energy resources (DERs), such as thermostatically controlled loads (TCLs) and storage devices, bid into an energy market. Consequently, a certain level of demand will be cleared based on the operating conditions of the grid. This paper analyzes the influence of various factors, such as price signals, feeder limits, and user-defined bid functions and preferences, on the aggregate energy usage of DERs. We identify cases that can lead to load synchronization, undesirable power oscillations and highly volatile prices. To address these issues, the paper develops an aggregate model of DERs under transactive coordination. A set of Markov transition equations have been developed over discrete ranges (referred to as "bins") of price levels and their associated DER operating states. A detailed investigation of the performance of this aggregate model is presented. With reformulation of the transition equations, the bin model has been incorporated into a model predictive control setting using both mixed integer programming and quadratic programming. A case study shows that a population of TCLs can be managed economically while avoiding congestion in a distribution grid. Simulations also demonstrate that power oscillations arising from synchronization of TCLs can be effectively avoided.

Role and Benefits of Flexible Thermostatically Controlled Loads in Future Low-Carbon Systems

Thermostatically controlled loads (TCLs) represent a valuable source of flexibility for the system. Depending on network needs, these devices could alter their nominal energy consumption and provide multiple ancillary services, facilitating the cost-effective transition to a low-carbon power system. Previous work mainly focused on investigating single service provision from TCLs, while intersections among different services have not been considered. Furthermore, the intrinsic energy payback effect was not fully included within optimisation tools for TCL scheduling. This paper presents a novel demand side response model (DSRM), which enables the optimal scheduling of energy/power consumption of a heterogeneous population of TCLs and the simultaneous allocation of multiple ancillary services. The model explicitly considers the effect of the energy recovery after delivering the services so that the deliverability of scheduled services from TCLs is always guaranteed. The proposed DSRM is integrated into an advanced stochastic unit commitment model to investigate the system benefits of the flexibility from TCLs. Case studies demonstrate that: 1) time-varying provision of multiple services from TCLs significantly increases their benefits; 2) TCL operation which aims to minimise the amplitude of the energy recovery causes sub-optimal utilisation of the devices; and 3) ignoring the energy payback leads to overestimate the TCL value.

A phase model approach for thermostatically controlled load demand response

A phase model approach for thermostatically controlled load demand response

Load Following of Multiple Heterogeneous TCL Aggregators by Centralized Control

Aggregate thermostatically controlled loads (TCLs) are good candidates for providing load following services in power systems. This paper is concerned with the modeling, evaluation, and control problems of a population of heterogeneous TCLs. Specifically, the heterogeneous population is divided into multiple homogeneous clusters and each cluster, i.e., TCL aggregator, is modeled by an approximated three-input single-output state space model. Here, the aggregators serve as a bridge connecting the load utility and the terminal TCLs, which have their own decision makers and are responsible for aggregate estimation and command issuing. And aggregate evaluation is carried out for the aggregator so as to provide the aggregate regulation capacities and ramping rates, which is useful for setting of the reference power trajectory. Based on the established control model, we furthermore propose a hierarchical centralized control algorithm for a bus load utility to regulate all TCLs inside it so as to provide load following service, while not affecting the customers’ comfort levels. Finally, simulation results with respect to a common bus load are provided to demonstrate the effectiveness of the proposed aggregate modeling and the centralized load following strategy.

Demand Response Using Heterogeneous Thermostatically Controlled Loads: Characterization of Aggregate Power Dynamics

This article presents an analysis of the damping and beating effects within the aggregate power demand of heterogeneous thermostatically controlled loads (TCLs). Demand response using TCLs is an appealing method to enable higher levels of penetration of intermittent renewable resources into the electric grid. Previous literature covers the benefits of TCL population heterogeneity for control purposes, but the focus is solely on the damping observed in these systems. This work, in contrast, characterizes the combined damping and beating effects in the power demand for different types of TCL parameter heterogeneity. The forced aggregate dynamics of TCLs have been shown to be bilinear when set point temperature adjustment is used as a control input. This motivates the article's use of free response dynamics, which are linear, to characterize both the damping and beating phenomena. A stochastic parameter distribution is applied to the homogeneous power demand solution, furnishing an analytic expression for the aggregate power demand. The time-varying damping ratios of this reduced-order model characterize the damping in the system. By analyzing a variety of case studies, it is determined that only a distribution of the TCL characteristic frequency creates damping in the aggregate power dynamics. The beating effect decays over time due to damping, and a relationship between the beat's amplitude and period is presented.

Generation following with thermostatically controlled loads via alternating direction method of multipliers sharing algorithm

Generation following with thermostatically controlled loads via alternating direction method of multipliers sharing algorithm

A Stability Analysis of Thermostatically Controlled Loads for Power System Frequency Control

Thermostatically controlled loads (TCLs) are a flexible demand resource with the potential to play a significant role in supporting electricity grid operation. We model a large number of identical TCLs acting autonomously according to a deterministic control scheme to provide frequency response as a population of coupled oscillators. We perform stability analysis to explore the danger of the TCL temperature cycles synchronising: an emergent phenomenon often found in populations of coupled oscillators and predicted in this type of demand response scheme. We take identical TCLs as it can be assumed to be the worst case. We find that the uniform equilibrium is stable and the fully synchronised periodic cycle is unstable, suggesting that synchronisation might not be as serious a danger as feared. Then detailed simulations are performed to study the effects of a population of frequency-sensitive TCLs acting under real system conditions using historic system data. The potential reduction in frequency response services required from other providers is determined, for both homogeneous and heterogeneous populations. For homogeneous populations, we find significant synchronisation, but very minimal diversity removes the synchronisation effects. In summary, we combine dynamical systems stability analysis with large-scale simulations to offer new insights into TCL switching behaviour.

Demand Response of a TCL Population Using Switching-Rate Actuation

This paper considers the problem of actively managing the power consumption of a large number of thermostatically controlled loads (TCLs), namely, a TCL population and a case study of household refrigerators. Control is performed using a new randomized actuation that consists of switching units ON and OFF at given rates, while at the same time respecting the nominal constraints on each individual unit. Both the free and the controlled behavior of individual TCLs can be aggregated, making it possible to handle a TCL population as if it were a single system. The aggregation method uses the distribution of the TCLs individual states across the population. The distribution approach has two main advantages. It scales excellently, since the computational requirements do not increase with the number of units, and it allows data from individual units to be used anonymously, which solves privacy concerns relevant for consumer adoption.