Article

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

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Abstract

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 models 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 (ASUC) 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, 3) ignoring the energy payback leads to overestimate the TCL value.

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... There is an extensive literature on providing grid services from cyclic loads, particularly TCLs. For example, research has shown that TCL aggregations can arbitrage dynamic energy prices [5]- [8], track aggregate power reference signals for frequency regulation or renewable supply following [8]- [16], and reduce peak demand [16]- [28]. This literature review focuses on the peak shaving studies [16]- [28], as they are most relevant to the current scope. ...
... There is an extensive literature on providing grid services from cyclic loads, particularly TCLs. For example, research has shown that TCL aggregations can arbitrage dynamic energy prices [5]- [8], track aggregate power reference signals for frequency regulation or renewable supply following [8]- [16], and reduce peak demand [16]- [28]. This literature review focuses on the peak shaving studies [16]- [28], as they are most relevant to the current scope. ...
... and s (k) ≥ s (k) 0 otherwise. (8) Constraints are accommodated by allowing the priority scores to take on infinite values. If load must (or must not) run, for example to respect a short-cycling constraint, then it sets s (k) = ∞ (or −∞). ...
Article
Analogous to the way a good driver is aware of neighboring cars, electrical loads can coordinate with other loads within a building or section of a distribution grid. This paper develops methods that enable groups of cyclic loads (devices that turn on and off periodically to maintain setpoints) to reduce their peak aggregate power demand. The methods accommodate a wide variety of cyclic loads, including those with nonlinear or unknown dynamics, and can be implemented in a fully distributed fashion. This paper targets settings with a few hundred cyclic loads or fewer, where the methods developed here could reduce demand peaks significantly while maintaining or improving quality of service. This could save ratepayers money on monthly demand charges, decrease fuel use in microgrids, or extend the life of power delivery equipment.
... For example, air conditioners (ACs) can be actively controlled to adjust their power consumption by changing their set temperature [7]. The aggregate reserve capacity would be large since the electricity consumption from ACs typically accounts for 35% in China [8]- [10]. However, the rebound effects may occur in the aggregate response of ACs for the provision of operating reserve [8]. ...
... The aggregate reserve capacity would be large since the electricity consumption from ACs typically accounts for 35% in China [8]- [10]. However, the rebound effects may occur in the aggregate response of ACs for the provision of operating reserve [8]. This phenomenon is the power rebound that arises when a large number of loads are re-connected to the grid at approximately the same time [9]. ...
... All of the MTCLs in each end-user residential unit are aggregated and abstracted as a load node. The aggregate power of this node depends on the operation form of these MTCLs, as shown in equation (7) and (8). ...
Article
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Electricity-driven thermostatically controlled loads (TCLs), e.g., air conditioners (ACs), have been widely utilized in demand response (DR) to provide operating reserve for power systems. However, the rebound effects may occur during the recovery process of DR, which can limit the operating reserve quality of ACs or even affect the reliable operation of power systems. With the community-level smart energy hubs (EH), the traditional electricity-driven TCLs can be expanded into multi-energy driven thermostatically controlled loads (MTCLs), e.g., household radiators. Under this circumstance, integrated demand response (IDR) can be exploited to coordinate the operation of MTCLs and provide more operating reserve resources while mitigating rebound effects. To this end, this paper proposes a two-stage IDR strategy to fully excavate the operating reserve provided by MTCLs. The first stage is to coordinate the energy consumption of ACs and household radiators to maximize the end-users’ thermal comfort and mitigate the rebound effects. To quantify the end-users’ thermal comfort, a modified predicted percentage of dissatisfied (PPD) index related to thermal environment parameters is introduced and simplified. Based on the energy consumption determined in the first stage, the energy conversion in EH is optimized in the second stage. Through the optimization in these two stages, a series of indices is established to evaluate the operating reserve in terms of aggregate capacity, duration, ramp rate, and smoothness. The case studies demonstrate that the proposed two-stage IDR strategy can provide high-aggregate-capacity and long-duration reserve resources in power systems while mitigating the rebound effects to maintain supply-demand balance and reliable operation of power systems. The analysis results of the test system show that the reserve capacity and duration obtained by the proposed model are 1.85 and 2.61 times those of the model without considering the multi-energy conversion, respectively.
... Alternatively (e.g., [24] and [17]), the generation commitment decisions and the allocation of ancillary services do not fully recognise the impact of the NI on post-fault frequency dynamics. Some of these issues were partially solved in [28] and [29]. However, these works focused on the value of TCL flexibility in an isolated power system, thus neglecting potential synergies and/or conflicts with flexible HVDC operation. ...
... Concerning the second research gap, previous models were not able to provide price signals to inform about the economic value for flexible assets and ancillary services. SCUC models are typically formulated as MILP optimisation problems (e.g., [30,28,31]). Although these models capture very accurately most of the actual system requirements, they often quantify the benefits of flexibility only by means of an overall indicator, i.e., the annual total cost savings. ...
... This is for instance different from the analysis in [35] which evaluates the economic value of responsive HVDC links through historic prices for frequency services. V The proposed SCUC expands the results in [28] by developing a set of system level NI-dependant constraints on frequency dynamics that also includes large infeed load losses (i.e., causing upwards frequency deviations). Hence, the demand side response model for TCLs developed in [28] is modified to integrate new dynamics of the TCL thermal energy and power. ...
Article
The replacement of conventional synchronous generators with converter-interfaced generation units calls for increased amounts of flexibility. This paper proposes a novel formulation of the security-constrained unit commitment (SCUC) model applied to a multi-area power system connected via High Voltage Direct Current (HVDC) links. From a system perspective, this paper provides a critical analysis of the synergies and differences between the exploitation of thermostatic loads and HVDC links when providing different layers of flexibility to the system. The former units operate within a local dimension, while the latter enable cross-border exchange of flexibility. Eight different ancillary services are modelled to tackle generation/load outages and uncertainty/variability in renewable energy output. The model is applied to the Great Britain network, which is connected to the Irish network and to the one in Continental Europe. Results suggest a critical review of the operation of future low-carbon HVDC-interconnected systems. Feasibility studies on the benefit for interconnection should no longer neglect considerations on local post-fault frequency dynamics in each area of the system. Then, fundamental changes to the mechanisms that price ancillary services become necessary in order to align these mechanisms with the technical needs of the system.
... e literature [8] proposes a demand response scheme using a hopping scheme for consumption scheduling of appliances which can protect the privacy of electricity consumers. e literature [9] proposes a novel demand-side response model, which can be integrated into system scheduling model straightway and enables the optimal scheduling of energy/power consumption of a heterogeneous population of TCLs. e literature [10] analyzes and studies the load control technology of central air conditioning based on demand response. ...
... In equation (9), UT k represents the minimum operating time of the k-th central air conditioning refrigerating machine; U 0 k represents the initial operating time of the k-th central air conditioning refrigerating machine; S(k, 0) represents the initial operating state of the k-th central air conditioning refrigerating machine; and G k refers to the required operating time at least of the refrigerating machine in order to keep continuous with the operating state before control during the initial period after the start of the control. e third expression in equation (9) is to ensure that the operation state of the central air conditioning unit remains continuous before the end of the controlled state. ...
Article
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In recent years, with the continuous growth of China’s power peak load and the rapid development of renewable energy, a large number of renewable energy sources are connected to the power grid, increasing the uncertainty of power grid operation and posing new major challenges to the power system regulation capacity. Flexible load has the characteristics of wide distribution, fast response, and high economy, which is an important control resource for the future power system. Based on the flexible load of commercial buildings and residential users, this paper studies the resource characteristics and response characteristics, clarifies the resource characteristics and demand response characteristic indexes of commercial and residential users, and establishes the response characteristics model of commercial buildings and residential users. Considering the influence of weather, holidays, incentive mechanism, and other factors on the response of flexible load, the quantitative analysis method of flexible load resource regulation potential for regional power grid dispatching was studied, and the feasibility of flexible load resources directly participating in the load control system was analyzed. Based on the uncertainty and mathematical characterization method of the active response of flexible loads, the optimal combination control strategy of demand response resources was proposed to eliminate the problems of heavy load and overload of regional power grid equipment by using the active response ability of flexible loads. Finally, the IEEE 14-node system is selected for simulation verification, which provides a theoretical basis for alleviating the power grid operation pressure in the peak load period of the power grid in the urban core area, improving the safety and economic operation level of regional power grid dispatching and the utilization rate of power grid equipment assets.
... In [9], an analytical approach is developed to characterize and control the reserve capacity of TCLs. A demand-side response model is proposed for TCLs to enable optimal scheduling of power and energy consumption and provide multiple ancillary services in [10]. A virtual battery (VB) model has also been proposed to quantify flexibility from building loads with diversified dynamics, constraints, and characteristics. ...
... 8: case P must-on + P on ≤ P * < P must-on + P on + P p : 9: Select all TCLs in TCL on ; select the first several TCLs in TCL p until the total power consumption is equal P * − P must-on − P on . 10: case P must-on +P on +P p ≤ P * < P must-on +P on +P p +P off : 11: Select all TCLs in TCL on and TCL p ; select the first several TCLs in TCL off until the total power consumption is equal P * − P must-on − P on − P p . 12: case P must-on + P on + P p + P off ≤ P * : 13: Select all TCLs in TCL on , TCL p , and TCL off . ...
Article
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A virtual battery model is a simple and general method to quantify aggregate flexibility from thermostatically controlled loads (TCLs), enabling grid operators to effectively coordinate a large number of flexible building loads with supplyside resources in power systems. Lockout controls are designed to avoid wear and tear resulting from short-cycling of hardware. The lock on/off time could significantly affect aggregate flexibility from TCLs to provide ancillary services and may even fail control algorithms designed without considering the lock time constraints. This paper focuses on flexibility estimation and control design for TCLs with lock time constraints to provide frequency regulation service. We first investigate the potential impacts of lock time on TCLs’ aggregate flexibility and control performance. Both control-dependent and control-independent power bounds are then derived, based on previous TCL switching operations and regulation signals, respectively. While the controldependent method provides aggregate flexibility for a given control method, the control-independent method calculates the theoretical maximum of power bounds. Finally, two control algorithms are proposed to better distribute flexibility over time and thereby improve signal tracking performance. The proposed methods are illustrated and validated through simulations.
... In recent years, mitigating actions have been investigated leading to improvements of forecast models [5][6][7]. On the other hand, efficient regulatory frameworks, which allow for re-dispatch updates closer to real-time operation have been proposed [8,9]. These measures may not directly tackle the second fundamental characteristic of renewables sources, i.e. the variability of their output. ...
... Although the financial viability of the investment is evaluated over Y = 20 years, the optimal operation of the RESS is assessed for a 24 h horizon formed by T = 48 SPs of 0.5 h each. Moreover, simulations are carried out with a rolling-planning approach [9], i.e. we perform a complete optimisation over the 48 time steps indexed bŷ ∈ = … t T T {1, , }, discarding all decisions beyond the first SP. This strategy is particularly beneficial due to the time-increasing nature of the forecast error of the renewable output. ...
... The comprehensive case studies demonstrate that the time-varying provision of multiple ancillary services from TCLs could significantly increase their benefits. 23 Qureshi and Jones proposed a hierarchical control scheme to provide ancillary services using building TCLs. The local building controllers at the lowest level track the temperature setpoints received from the thermal flexibility controller which maximizes the flexibility of building's thermal consumption. ...
... Step 4: If the EV did request recharging and the request was granted, a routing planning software package such as Trovato et al. 23 will be used to estimate the time from the current location to the charging point. Otherwise, proceed to Step 7. ...
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With the rapid development of the emerging technologies and significant cost reduction of the deployment for solar energy and wind power, the replacement of traditional power generation by renewable energy becomes feasible in the future. However, different from currently deployed centralized power sources, renewables are categorized as one kind of intermittent energy sources, and the scale of renewables is small and scattered. In the recent literature, the architecture of virtual power plant was proposed to replace the current smart grid in the future. However, the energy sharing concept and the uncertainties of intermittent energy sources will cause the short-term energy management for the virtual power plant much more complicated than the current centralized control energy management for traditional power generation system. We thus propose a hierarchical day-ahead power scheduling system for virtual power plant in this work to tackle the complex short-term energy management problems. We first collect electricity consumption data from smart appliances used in households and predict power-generating capacity of renewable energy sources at the prosumer level. Then, the proposed hierarchical power scheduling system is employed to schedule the usage of electricity for the customers by considering the efficiency of the use of distributed renewables. Notably, charging management of a moving electric vehicle is also considered in the proposed power scheduling mechanism. In addition, a real-time power tracking mechanism is presented to deal with the forecast errors of volatile renewable power generation, electricity load, and moving electric vehicle charging, and the maximal usage of renewables and reduction of the burden on community virtual power plants during time period of peak load can be achieved accordingly. The experimental results show that the proposed day-ahead power scheduling system can mitigate the dependency on traditional power generation effectively, and balance peak and off-peak period load of electricity market.
... The application of multi-energy microgrid (MEMG) provides an important avenue to improve operational flexibility. It is inevitable to tap the flexibility potential of the MEMG system and fully plan the flexible resources in the scheduling process (Holttinen et al., 2013;Ma et al., 2013;Lund et al., 2015;Trovato et al., 2018), which implies the requirement of formulating a reasonable method to evaluate the flexibility margin of flexible resources in the MEMG system. ...
Article
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Today’s power system is facing various challenges brought by large-scale renewable energy (RE) integration, which brings higher demand for flexibility. With the energy network gradually showing its distributed structural characteristics, multi-energy microgrids (MEMG) become an important component to effectively utilize distributed energy sources and supplement the flexibility of power distribution system (PDS). To effectively harness the operational flexibility of distributed MEMGs, we propose in this paper an evaluation method to quantify the flexibility capability of MEMG. A virtually established MG flexibility bus (MG-FB) is endowed with MG flexibility parameters (MG-FPs), which can reflect the flexibility characteristics of MEMG. To consider the impact of operational uncertainty on MG-FPs, a two-stage adaptive robust optimization (ARO) model is proposed, which can be solved by the C&CG algorithm. The results of a typical test system show the influence of system configuration, operator’s risk preference, and other factors on the values of MG-FPs. Besides, we illustrate the effectiveness and applicability of the proposed framework in modeling and quantifying the operational flexibility of MEMG to support the operation of the upstream network.
... In [4], a bi-level scheduling approach for aggregating a large number of TCLs was presented, while a two-stage optimization model of the distribution network considering the coordination of multiple TCL groups was proposed in [5]. A linear optimization model was established in [6] for the provision of frequency response ii through refrigerators, while demand side response through collective operation of diversified TCLs was proposed in [7]. There are some other literature focused on controller design which enables TCLs to accurately deliver some functionalities. ...
Preprint
Full-text available
Demand-side response from space heating in residential buildings can potentially provide a huge amount of flexibility for the power system, particularly with deep electrification of the heat sector. In this context, this paper presents a novel distributed control strategy to coordinate space heating across numerous residential households with diversified thermal parameters. By employing an iterative algorithm under the game-theoretical framework, each household adjusts its own heating schedule through demand shift and thermal comfort compensation with the purpose of achieving individual cost savings, whereas the aggregate peak demand is effectively shaved on the system level. Additionally, an innovative thermal comfort model which considers both the temporal and spatial differences in customised thermal comfort requirements is proposed. Through a series of case studies, it is demonstrated that the proposed space heating coordination strategy can facilitate effective energy arbitrage for individual buildings, driving a 13.96% reduction in system operational cost and 28.22% peak shaving. Moreover, the superiority of the proposed approach in thermal comfort maintenance is numerically analysed based on the proposed thermal comfort quantification model.
... TCLs by Trovato et al. (2018) to enable optimal scheduling of power and energy consumption and to provide multiple ancillary services. When scheduling a large group of TCLs for grid services, it is computationally expensive yet unnecessary to model and consider detailed dynamics and constraints of individual devices. ...
Article
Full-text available
This paper presents a framework for modeling, scheduling, and controlling residential thermostatically controlled loads (TCLs) to provide multiple grid services, such as energy shifting, peak load reduction, and ancillary services. A modeling method is proposed to characterize aggregate flexibility from heterogeneous TCLs using a virtual battery model. Based on the flexibility model, a multi-period optimal scheduling formulation is developed to best utilize the flexibility from building loads and maximize total benefits from stacked value streams. An algorithm is proposed to control individual devices to follow the desired power consumption in real-time. The proposed methods are illustrated and validated through simulations.
... However, an ex-ante dispatch decision was adopted, making the available inertial response a pre-determined quantity, i.e., not a decision variable of the optimisation problem. Furthermore, effective formulations have been introduced in Reference [ [24][25][26][27]. Regardless of the fundamental differences among these works, it is possible to highlight a common trait: the inertial response and its effect of post-fault frequency dynamics becomes a decision variable of a Unit Commitment (UC) problem. ...
Article
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Renewable integration into the electricity system of Great Britain is causing considerable demand for additional flexibility from plants. In particular, a considerable share of this flexibility may be dispatched to secure post-fault transient frequency dynamics. Pursuant to the unprecedented changes to the traditional portfolio of generation sources, this work presents a detailed analysis of the potential system-level value of unlocking flexibility from nuclear electricity production. A rigorous enhanced mixed integer linear programming (MILP) unit commitment formulation is adopted to simulate several generation-demand scenarios where different layers of flexibility are associated to the operation of nuclear power plants. Moreover, the proposed optimisation model is able to assess the benefit of the large contribution to the system inertial response provided by nuclear power plants. This is made possible by considering a set of linearised inertia-dependent and multi-speed constraints of post fault frequency dynamics. Several case studies are introduced considering 2050 GB low-carbon scenarios. The value of operating the nuclear fleet under more flexible paradigms is assessed, including environmental considerations quantified in terms of system-level CO2 emissions’ reduction.
... e increasing penetration of renewable energy is conducive to sustainable economic development and the achievement of the "carbon neutrality" target [1]. However, the uncertainty, high fluctuations, and antipeak shaving characteristics of new energy generation seriously affect the safe and stable operation of the grid [2]. Using conventional generating units to participate in grid regulation has become more difficult, and the potential for demand-side resources to contribute to grid regulation needs to be explored [3]. ...
Article
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In order to deal with the fluctuation of the renewable energy, this paper proposes rolling scheduling strategy taking into account the capacity of load-side resources. By considering the energy characteristics of shiftable loads, an improved rolling scheduling model is proposed by adopting a full-cycle scheduling and adding periodic power constraints. By this way, the accuracy of the scheduling can be improved. The testing examples verified that the proposed rolling scheduling method can reflect the long-time benefit and therefore result in better performance.
... Moreover, the exact mapping of the aggregate TCL population onto a 'leaky battery' representation [17] means that both response and recharging can be scheduled optimally according to aggregator objectives. Trovato et al. [27] have used this to optimally schedule primary and secondary response in the Great Britain system and calculate the associated benefits. The ability of some TCLs (e.g. ...
Preprint
Thermostatically controlled loads such as refrigerators are exceptionally suitable as a flexible demand resource. This paper derives a decentralised load control algorithm for refrigerators. It is adapted from an existing continuous time control approach, with the aim to achieve low computational complexity and an ability to handle discrete time steps of variable length -- desirable features for embedding in appliances and high-throughput simulations. Simulation results of large populations of heterogeneous appliances illustrate the accurate aggregate control of power consumption and high computational efficiency. Tracking accuracy is quantified as a function of population size and time step size, and correlations in the tracking error are investigated. The controller is shown to be robust to errors in model specification and to sudden perturbations in the form of random refrigerator door openings.
... The availability and benefits from electric space, water heating, cold and wet appliances to participate in GB balancing market have been analyzed in [2]. The overall system benefits of multiple services provision from thermostatically-controlled loads [3], electrified transportation and heating [6] as well as generic demand-side response [7] have been investigated using an advanced Stochastic Unit Commitment (SUC) model. Nonetheless, Enhanced Frequency Response (EFR), introduced by National Grid GB in 2017 [8], has not been considered in the above study. ...
... The availability and benefits from electric space, water heating, cold and wet appliances to participate in GB balancing market have been analyzed in [2]. The overall system benefits of multiple services provision from thermostatically-controlled loads [3], electrified transportation and heating [6] as well as generic demand-side response [7] have been investigated using an advanced Stochastic Unit Commitment (SUC) model. Nonetheless, Enhanced Frequency Response (EFR), introduced by National Grid GB in 2017 [8], has not been considered in the above study. ...
Preprint
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The need for Enhanced Frequency Response (EFR) is expected to increase significantly in future low-carbon Great Britain (GB) power system. One way to provide EFR is to use power electronic compensators (PECs) for point-of-load voltage control (PVC) to exploit the voltage dependence of loads. This paper investigates the techno-economic feasibility of such technology in future GB power system by quantifying the total EFR obtainable through deploying PVC in the urban domestic sector, the investment cost of the installment and the economic and environmental benefits of using PVC. The quantification is based on a stochastic domestic demand model and generic medium and low-voltage distribution networks for the urban areas of GB and a stochastic unit commitment (SUC) model with constraints for secure post-fault frequency evolution is used for the value assessment. Two future energy scenarios in the backdrop of 2030 with `smart' and `non-smart' control of electric vehicles and heat pumps, under different levels of penetration of battery energy storage system (BESS) are considered to assess the value of PEC, as well as the associated payback period. It is demonstrated that PVC could effectively complement BESS towards EFR provision in future GB power system.
... As for typical demand response (DR) resources, thermostatically controlled loads (TCLs), e.g. air conditioners, refrigerators and water heaters, provide promising opportunities to compensate power imbalances triggered by wind generation variabilities [3], [4] . ...
... Still, generation and consumption must be balanced at a seconds time scale, especially when inertia is reduced in the grid. The shortterm flexibility offered by HEMS/HVAC systems is increasingly exploited for fast balancing or frequency response [9,21,133,134,146,147]. If the flexibility is an essential service but drawn on irregularly and for short time spans, it cannot be valued by duration (energy tariff) but rewarded through contractual incentives [30,148]. ...
Article
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Power imbalances from fluctuating renewable electricity generators are counteracted by often expensive flexibility services. Heating, cooling, and air-conditioning (HVAC) of buildings, or domestic power-to-heat (P2H), are end uses of electricity that allow flexible load patterns due to the inertia of an attached thermal storage while meeting their quality constraints. Compared to smart appliances or electric vehicle charging, P2H exhibits large and predictable capacities of demand response (DR), because buildings in many countries account for 30–40% of the final energy demand, a large part of which is thermal. Yet, its practical flexibility potential remains largely unknown: is DR from P2H a mature technology for mass usage; is it cost-efficient, socially attractive, and ready to make key contributions to flexibility comparable to backup generators or battery storage? In the present paper, we review recent international field studies that are paving the way from research to practice. These field trials include real customers but have a broader research focus and a wider outreach than rolling out a new DR tariff or program or a specific new technology for DR. Their experience mirrors the technology readiness beyond revenue or policy studies, optimization frameworks or laboratory-scale micro-grids. We analyze the adequacy of the pricing mechanisms deployed for incentivization and remuneration and review the coordination mechanisms for balancing on different timescales including fast ancillary services. We conclude that current control and information technology and economic and regulatory frameworks which have been field-tested do not yet meet the flexibility challenges of smart grids with a very high share (>50%) of intermittent renewable generation.
... For frequency response, in terms of residential TCLs, [18] and [19] investigated the potential and developed design considerations and parameter selection for residential air conditioners to provide load following and secondary frequency control services. [20] and [21] evaluated economic and environmental benefits of residential refrigerators that provides primary frequency control services in the future GB power system. [22] [25], supply pressure / mass flow setpoint offset [25], [26] and thermostat setpoint offset [27], [28]. ...
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Increasing penetration of renewable generation results in lower inertia of electric power systems. To maintain the system frequency, system operators have been designing innovative frequency response products. Enhanced Frequency Response (EFR) newly introduced in the UK is an example with higher technical requirements and customized specifications for assets with energy storage capability. In this paper, a method was proposed to estimate the EFR capacity of a population of industrial heating loads, bitumen tanks, and a decentralized control scheme was devised to enable them to deliver EFR. Case study was conducted using real UK frequency data and practical tank parameters. Results showed that bitumen tanks delivered high-quality service when providing service-1-type EFR, but underperformed for service-2-type EFR with much narrower deadband. Bitumen tanks performed well in both high and low frequency scenarios, and had better performance with significantly larger numbers of tanks or in months with higher power system inertia.
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This letter presents analytical solutions for fast quantification of load flexibility of building air-conditioning systems, considering the second-order building dynamics. Two equations are derived to quantify the load reduction and subsequent load rebound of individual buildings, respectively, as functions of regulation durations and indoor air temperature offset. An equation is derived to explicitly represent the coupling between the aggregated load reduction and rebound of buildings, facilitating the incorporation of load flexibility into power system scheduling. Numerical simulations verify the superior accuracy and computational efficiency of the analytical solutions.
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Thermostatically controlled loads (TCLs) are deemed as essential flexible resources on the demand side that can facilitate the cost-effective transition to a low-carbon power system. However, integrating massive TCLs into the optimal operation of active distribution network (ADN) is challenging due to uncertainty and computation complexity. A reliable and efficient TCLs aggregation technique is the key enabler. Firstly, this paper proposes an improved aggregation approach that introduces the minimal representation and reconstruction operations of polytopes to boost the aggregation efficiency. In addition, the uncertainties of outdoor temperature and indoor heat loads are comprehensively considered via the derived distributionally robust joint chance constraints with optimized violation probability. Then, in the coupled electricity-carbon market environment, a two-stage ADN scheduling model is established, which facilitates the realization of economic operation and environmental friendliness of the system using the distribution locational marginal price and nodal carbon intensity signals. To solve the developed scheduling model, a customized bisection-based iterative method is designed to avoid possible oscillations. Case studies illustrate that the proposed approach leads to higher profits and lower carbon emissions for TCLs aggregators than traditional methods while maintaining users' thermal comfort.
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The significant reduction in the system inertial response due to the increasing penetration of converter-interfaced renewable generators may reduce the ability to safely control post-fault frequency dynamics. Larger volumes of flexible ancillary services may be required to ensure system stability. Part of these additional regulation resources may be procured from other power systems by means of existing and new interconnectors. The paper investigates this framework by assessing the techno-economic benefits of interconnectors that operate in a multi-area power network and whose capacity can be utilized for simultaneous exchange of power and fast-frequency services. Two different operational approaches are considered: a traditional centralized allocation of the interconnectors' capacity and an alternative market-based paradigm where price-making interconnectors act as profit-seeking agents that aim to maximize their collected congestion surplus. The paper provides new fundamental results on the benefits of a multi-purpose allocation of the interconnectors' capacity, directly comparing the operational choices and the interactions between centrally-operated and self-interested interconnectors, and quantifying the impact of the latter on the overall social welfare of the system. This novel methodology is applied to a model of an interconnected Great Britain-France-Ireland multi-area system, quantifying the potential benefits of multi-service interconnectors and assessing the impact of their self-interested scheduling within a realistic framework that considers power systems of different sizes and characteristics.
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Second-to-second renewable power fluctuations can severely hinder the frequency regulation performance of modern isolated microgrids, as these typically have a low inertia and significant renewable energy integration. In this context, the present paper studies the coordinated control of Thermostatically Controlled Loads (TCLs) for managing short-term power imbalances, and their integration in microgrid operations through the use of aggregate TCL models. In particular, two computationally efficient and accurate aggregate TCL models are developed: a virtual battery model representing the aggregate flexibility of TCLs considering solar irradiance heat gains and wall/floor heat transfers, and a frequency transient model representing the aggregate dynamics of a TCL collection considering communication delays and the presence of model uncertainty and time-variability. The proposed aggregate TCL models are then used to design a practical Energy Management System (EMS) integrating TCL flexibility, and study the impact of TCL integration on microgrid operation and frequency control. Computational experiments using detailed frequency transient and thermal dynamic models are presented, demonstrating the accuracy of the proposed aggregate TCL models, as well as the economic and reliability benefits resulting from using these aggregate models to integrate TCLs in microgrid operations.
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Demand side response from space heating in residential buildings can potentially provide huge amount of flexibility for the power system, particularly with deep electrification of the heat sector. In this context, this paper presents a novel distributed control strategy to coordinate space heating across numerous residential households with diversified thermal parameters. By employing an iterative algorithm under the game-theoretical framework, each household adjusts its own heating schedule through demand shift and thermal comfort compensation with the purpose of achieving individual cost savings, whereas the aggregate peak demand is effectively shaved on the system level. Additionally, an innovative thermal comfort model which considers both the temporal and spatial differences in customized thermal comfort requirement is proposed. Through a series of case studies, it is demonstrated that the proposed space heating coordination strategy can facilitate effective energy arbitrage for individual buildings, driving 13.96% reduction in system operational cost and 28.22% peak shaving. Moreover, the superiority of the proposed approach in thermal comfort maintenance is numerically analysed based on the proposed thermal comfort quantification model.
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Through the reasonable aggregation and control of air conditioning loads (ACLs), the peak load of power grid can be reduced and the contradiction between supply and demand can be alleviated without affecting or less affecting the comfort of users. In order to further tap the demand response ability of aggregated loads, an aggregation strategy of ACLs considering diversity of the load is proposed. Firstly, grey relational analysis method is used to extract the thermal environmental characteristic parameters with high correlation to different categories of ACLs. Then, ACLs are classified by KNN algorithm; Finally, according to different control modes of ACLs, k-means algorithm is used to aggregate the load to obtain aggregated power. Through simulation verification, the aggregation strategy that retains the diversity of ACLs has high accuracy and can improve the aggregated active power capacity effectively. The strategy has higher practical application value.
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Due to large thermal inertia of buildings and flexibility of interruptible loads, smart buildings pose a remarkable potential for developing virtual energy storage systems (VESSs). However, current literature lacks advanced models to quantify and thus properly optimize available capacity of VESS for power system ancillary services, especially frequency regulation services (FRS). This paper, firstly, presents a novel probabilistic model for explicitly quantifying the VESS capacity in charging and discharging modes, which can further be optimized by scheduling building loads. While the optimized capacity is fully available for FRS, building customer economic benefit and comfort could considerably be impaired by various uncertainties including weather and user related parameters, as well as FRS requests. Due to limited information of the uncertainties, common model-based stochastic and robust optimization approaches are inefficient, leading to either poor out-of-sample performance or over-conservative solutions. Thus, secondly, this paper develops a data-driven distributionally robust optimization (DRO) method to robustly optimize the capacity of VESS against the worst distribution of the uncertainties with a finite training dataset. The proposed data-driven DRO-based model can well match modern data-driven operation environment. Numerical simulations validate the high efficiency and out-of-sample performance of the proposed VESS capacity optimization method under the uncertainties.
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The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generations (DGs) and advancement of information and communication technology (ICT) even though handles the related issues and challenges up to some extent, till the flexibility, energy management and scheduling with better planning are necessary for the residential sector to achieve better grid stability and efficiency. To address these issues, it is indispensable to analyze the demand-side management (DSM) for the complex residential sector considering various operational constraints, objectives, identifying various factors that affect better planning, scheduling, and management, to project the key features of various approaches and possible future research directions. This review has been done based on the related literature to focus on modeling, optimization methods, major objectives, system operation constraints, dominating factors impacting overall system operation, and possible solutions enhancing residential DSM operation. Gaps in future research and possible prospects have been discussed briefly to give a proper insight into the current implementation of DSM. This extensive review of residential DSM will help all the researchers in this area to innovate better energy management strategies and reduce the effect of system uncertainties, variations, and constraints.
Article
Under future low-carbon scenarios, it will be crucial to boost the rapidity in the delivery of frequency response services, especially those provided by conventional generators. This paper proposes a novel framework for the scheduling of frequency response services that incentivizes a rapid response from different system assets, including conventional generators. Differently from other approaches which envisage a fixed delivery time for frequency response services, the proposed methodology implements time-varying delivery intervals, which coincide with the time of frequency nadir occurrence. A relevant set of linearized constraints is embedded in a typical power system scheduling model. Results indicate that the proposed methodology reduces the unnecessary overscheduling associated with traditional methodologies, leading to significant operational cost savings.
Chapter
TCLs can respond to control signals quickly by on–off switches to provide fast regulation service. A uniform-time state bin aggregate model (UTIM) with higher accuracy is introduced and the corresponding modelling constraints are first presented. Then, based on the UTIM, a novel aggregated control model that takes into account both the external control signals and the time delay of TCL compressor is proposed to follow the dynamic collective behavior of TCLs, which will make the UTIM more practical and accurate. To relieve the communication burden and reduce the number of switching times, a generalized control method is also proposed to control TCLs through the global signal. The simulation results show that the novel aggregate control model can track the collective performances of TCLs more closely, taking the time delay of the compressor into account. Additionally, the proposed control method requires fewer control signals and switching times.
Chapter
To address the microgrid tie flow errors caused by wind generation variability, this chapter proposes and develops a multi-time scale coordinated control and scheduling strategy of inverter TCLs. First, in hour-time scale, inverter-based TCLs with adjusting temperature set-point are modeled as virtual generators to compensate for the tie flow deviations from the day-ahead plan. Next, in a minute-time scale, virtual batteries representing the operating behavior of inverter-based TCLs with frequency control are determined by the control of virtual generators in an hour-time scale. The virtual batteries are scheduled to smooth out tie flow errors corresponding to the day-ahead plan and hour-time scale scheduling. In this work, multi-time scale control methods are coordinated to employ the response potential of inverter-based TCLs. And transactive scheduling based on the response curve is proposed to regulate inverter TCLs considering customer privacy. The multi-time scale stochastic scheduling of TCLs is coordinated to accommodate wind generation variability. Simulation results demonstrate that the microgrid tie flow errors are effectively mitigated by the proposed multi-time scale coordinated control and scheduling of inverter TCLs.
Chapter
TCLs have attracted additional attention in power system operations, mainly due to their flexibility in supplying DR. Determining accurate parameters for the aggregated TCL population is thus crucial. It 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 chapter 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 that 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 to reduce 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; (3) TCL power capacity can be calculated quickly via HDMR in various dispatch periods.
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Integrating large amounts of volatile renewable power into the electricity grid requires ancillary services (AS) from multiple providers including flexible demand. These should be comparable by uniform and efficiently evaluable performance criteria. The objective is to characterize the technical flexibility of aggregated building heating, ventilation, and air-conditioning (HVAC) under different operating conditions. New bounds of flexible power and holding durations, accordingly pay-back power and recovery times, and ramping rates are derived, using a new gray-box model of stochastically actuated aggregations of thermostatically controlled loads (TCL) that can serve as well for load control. New closed formulas of the expected switching temperatures are derived using survival processes and hazard functions. The distribution of holding durations (HDD) for a given load deviation refines and tightens constant energy bounds, and the HDD order statistics allows statistical guarantees for heterogeneous TCL populations. This ex-ante characterization enables fast decision tools for AS feasibility testing and planning by demand aggregators, as it does not rely on simulation or optimization, nor on the identification and clustering of unit-level parameters. The estimates are explored in a sensitivity study of urban-level heat pump heating with respect to six key input factors. A case study using dynamic regulation signals from Pennsylvania-New Jersey-Maryland (PJM) demonstrates the benefit, in terms of tracking precision, of the refined energy measures over pure energy or power capacity bounds. This article is protected by copyright. All rights reserved.
Article
This paper presents a unified state space model for aggregation and coordination of large-scale thermostatically controlled loads (TCLs) and electric vehicles (EVs) to jointly participate in the frequency regulation of power systems. The proposed approach is characterized by low communication requirements and an accurate regulation capacity estimation. In order to perform the coordination with minimum communication burden, two distinct control signals, namely TCL-control signal and EV-control signal are developed. The former is communicated to all individual TCLs while the latter is communicated to all individual EVs. The simulations are conducted for a community-level microgrid including a large population of TCLs and EVs, a conventional generator and a wind generation system. It is shown that the proposed control structure can accurately describe the aggregated behaviour of a large population of TCLs and EVs and can efficiently counteract the frequency deviations. Moreover, the proposed control structure reduces the excessive dependence on one type of resource, minimizes the short cycling of TCLs, guarantees the energy requirements of the EVs and respects the energy constraints of the EV batteries.
Article
Multi-energy flexibility measures comprising energy substitution and demand-side management (DSM) can enhance the control of buildings and help them participate in the energy market, obtaining greater profit margins. However, the application of these flexibility measures is also subject to many limitations. For example, DSM is a kind of load redistribution process in which the energy payback constraints associated with comfort or usage demand should be considered. Therefore, this work studies the optimal energy management of a building energy system (BES) considering multi-energy flexibility measures, specifically under the energy payback effect, to better guide the peak shaving strategies. First, energy substitution measures are proposed involving energy conversion and storage modeling. Second, a novel dynamic two-step DSM measure is modeled for the reduction and recovery process. Then, a mixed-integer and linear programming (MILP)-based energy management model is developed to optimize the operation of smart buildings for peak shaving. The case studies demonstrate that 1) a BES can obtain better profit by utilizing multi-energy flexibility measures; 2) optimized multi-load recovery strategies can enhance the flexibility potential of a BES; and 3) a reasonable multi-load recovery mechanism should be established to offset the energy payback effect.
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Thermostatically controlled loads such as refrigerators are exceptionally suitable as a flexible demand resource. This paper derives a decentralised load control algorithm for refrigerators. It is adapted from an existing continuous time control approach, with the aim to achieve low computational complexity and an ability to handle discrete time steps of variable length -- desirable features for embedding in appliances and high-throughput simulations. Simulation results of large populations of heterogeneous appliances illustrate the accurate aggregate control of power consumption and high computational efficiency. Tracking accuracy is quantified as a function of population size and time step size, and correlations in the tracking error are investigated. The controller is shown to be robust to errors in model specification and to sudden perturbations in the form of random refrigerator door openings.
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In smart grid era, demand side management (DSM) plays an indispensable role in development of sustainable cities and societies. This paper presents practical challenges imposed while implementing DSM using load shifting for IoT enabled home energy management systems (HEMS). The main objective of the manuscript is to provide thorough information to the researchers working towards the development of advanced and realistic optimization algorithms for DSM implementation. Here, the issues related to the characterization of home appliances, integration of intermittent renewable energy sources, load categorization, various constraints, dynamic pricing, consumer categorization has been discussed. DSM being a stochastic optimization problem, an extensive survey of different optimization techniques solving the multi-objective energy management problem has been discussed. The DSM implementation issues in distribution network, mainly related to grid constraints, consumer incentives and utility policies are described in detail. This manuscript also provides a deeper insight into challenges, constraints and future opportunities to meet the desired objectives of DSM.
Article
The increasing penetration of renewable generation presents challenges for system frequency regulation due to short-term power fluctuations and system inertia reductions. This paper presents a coordinated control strategy for frequency regulation in which inverter air-conditioning (IAC) units are used to perform primary frequency regulation (PFR) and fixed frequency air-conditioning (FFAC) units are used to perform secondary frequency regulation (SFR). In PFR, the regulation power is provided by adjusting the setpoints of the IAC units. A random number generation method is proposed to stochastically trigger IAC units based on the frequency deviation in real time. Furthermore, a recovery method is presented to stably restore the IAC units to their initial operating states after regulation. In SFR, a constant equivalent duty ratio method is raised to keep the regulation power stable over a long instruction interval. Based on this, the transforming time interval method is presented to determine the ON/OFF status of FFAC units to provide the required regulation power. Additionally, a recovery method for FFAC units is proposed to mitigate the power rebound after regulation. The proposed control strategy achieves an improved frequency regulation effect with fewer communication demands. Dynamic simulations in a six-machine two-area system and an isolated microgrid with wind power verify the effectiveness of the proposed control strategy.
Article
A novel hierarchical Energy Management System (EMS) framework is proposed for the incorporation of Thermostatically Controlled Loads (TCLs) in the provision of ancillary services (ASs), 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.
Article
The GB power blackout, that happened on 9 August 2019, was a unique stress test exposing fault lines brought about by the rapid changes due to the decarbonisation drive and penetration of smart grids technologies. It has demonstrated that, as a significant amount of new equipment and controls were added to the system in a very short time, the probability of common, hidden modes of failures has significantly increased. In the face of declining reliability, maintaining the status quo is not an option. While currently increasing the (N-1) security margin could prove to be expensive, the balance of costs and benefits is likely to change in future. Especially wider application of innovative frequency controls, including “virtual inertia” and Remedial Action Schemes, could help reduce the costs. Distributed Generation (DG) reached such a high penetration level that it cannot be treated any longer as negative demand. Traditional under-frequency load shedding should be made more selective. Interactions between the power system and other infrastructures are still poorly understood and there is a significant risk that if the current compartmentalised approach to their governance and operation is not changed, we may see more unexpected consequences of disturbances across the whole system.
Article
Since wind turbines or photovoltaic (PV) panels are generally connected to the power grid by power electronic inverters, the power system inertia is gradually decreasing along with the growing share of renewable energy. This jeopardizes the system frequency response dynamics so that the corresponding frequency security issue is becoming the bottle-neck factor that restricts the development of high renewable energy penetration. Consequently, power system scheduling models need to incorporate frequency dynamics. The difficulty lies in how to formulate the frequency security constraints from the perspective of hourly load-generation balance since the frequency dynamics have a shorter time scale (5~30 s). Several modeling methods have been proposed based on different assumptions and simplifications. However, their accuracy is not clear. We first propose a novel method to formulate linear frequency security constraints, which considers more details of frequency response dynamics. Then, an evaluation methodology is designed to quantify the accuracy of those frequency constraints. Using this evaluation method, we compare two typical methods in recent literature with the proposed method. The results show the effectiveness and superiority of our proposed method.
Chapter
Thermostatically controlled loads (TCLs) have been studied to provide operating reserve for maintaining power balance between supply and demand. However, operating reserve capacity (ORC) supplied by aggregated TCLs is difficult to evaluate, due to the insufficient information of heterogeneous TCLs and consumer behaviours. This chapter proposes a quantitative ORC evaluation method for large-scale aggregated heterogeneous TCLs without sufficient measurement data. Firstly, an individual TCL model on account of consumer behaviours is developed to characterize the impact of fluctuated electricity prices and different thermal comfort requirements. Secondly, a novel optimization model of heterogeneous TCLs, which can guarantee consumer satisfaction, is proposed to provide operating reserve for power systems. Thirdly, the probability density estimation (PDE) method is developed to evaluate the ORC provided by large-scale heterogeneous TCLs with insufficient data. Numerical studies illustrate the effectiveness of the proposed models and methods.
Chapter
Air conditioners (ACs) are widely considered as good candidates to provide operating reserve. Demand response rebound, i.e., the rebound peak of aggregate power, may exist when ACs are controlled by changing the set point temperature. The rebound peak during the recovery period, named as the lag rebound, may cause significantly higher demand than that prior to the reserve deployment event. The rebound peak during the reserve deployment period, named as the lead rebound, is rarely considered in previous researches but will constrain the duration time to a short period (e.g., 10 min), which greatly limits the utilization of ACs. This chapter proposes an optimal sequential dispatch strategy of ACs to mitigate the lead-lag rebound and thus realize flexible control of the duration time from minutes to several hours. To quantify the effects of lead-lag rebound, a capacity-time evaluation framework of the operating reserve is developed. On this basis, ACs are grouped to be dispatched in sequence to mitigate the lead-lag rebound. The co-optimization of sequential dispatch on the capacity dimension and time dimension forms a mixed integer nonlinear bi-level programming problem, in which the consumers’ thermal comfort is also guaranteed. Case studies are conducted to validate the proposed strategy.
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With the incorporation of higher shares of intermittent renewable energies (RES), more flexible resources are required in power systems to keep load balance. Under some extreme circumstances, the flexible demand resources (FDRs) may have the potential to dominate and obtain excess benefits, preventing other FDRs from participating in the electricity markets. Therefore, it is of great significance to identify the key FDR market power locations and implement some corresponding regulations. However, the relevant researches in power systems focused on the supply side, rather than the demand side. In this paper, a novel nodal market power analysis method is proposed to evaluate the potential influence of FDRs on electricity markets. Firstly, a multi-state model is established to present the multiple power system operation states including the random failures of system components. Then, the nodal market power assessment model is established under each specific state and new indices are proposed to evaluate the nodal market power of FDRs quantitatively. Furthermore, the key FDR nodes in demand side with stronger power in capturing excess revenue are identified. The 24-bus IEEE Reliability Test System is modified to demonstrate the feasibility of the proposed method. The numerical results of the proposed method are capable to display the existence of market power in demand side, and provide some valuable guidance for classification and operation of electricity markets.
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Bitumen tanks were tested to investigate the capability of industrial heating loads to provide frequency response to an electric power system. A decentralized control algorithm was developed enabling the tanks to alter their power consumption in proportion to the variations of grid frequency. The control maintains the normal operation of tanks and causes little impact on their primary function of storing hot bitumen. Field investigations were undertaken on 76 tanks with power ratings from 17 to 75 kW. A model of a population of controlled tanks was developed. The behavior of the tanks was compared between the simulations and the field tests. The model of controlled tanks was then integrated with a simplified Great Britain power system model. It was shown that the controlled tanks were able to contribute to the grid frequency control in a manner similar to and faster than that provided by frequency-sensitive generation.
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There are few systematic methodologies capable of predicting and leveraging the reserve capacity potential of large populations of thermostatically-controlled loads (TCLs). For such reserves to have economic and technical value, it is essential that demand-side flexibility aggregators and system operators be able to do so quickly and robustly. In addition, aggregators need to ensure TCL users' comfort and end use satisfaction. Part I of this two-part paper introduces an analytical approach to characterize and control the statistical bounds on the potential aggregated response of a population of TCLs, while ensuring users' comfort satisfaction. First, the uncertainty associated with the instantaneous power consumption of a typical TCL is described by a set of random variables and their statistics. TCL statistics are then employed to characterize the exploitable flexibility from a large population of similar devices. From this, a control strategy and parameters are introduced for sporadic (i.e., contingency-type) reserve provision by the population. In Part II, the proposed analytical approach and control strategy are validated for the special case of electric water heaters (EWHs). Further, the trade-off between demand response capacity and EWH users' comfort satisfaction is investigated through several case studies.
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Increasing levels of wind generation has resulted in an urgent need for the assessment of their impact on frequency control of power systems. Whereas increased system inertia is intrinsically linked to the addition of synchronous generation to power systems, due to differing electromechanical characteristics, this inherent link is not present in wind turbine generators. Regardless of wind turbine technology, the displacement of conventional generation with wind will result in increased rates of change of system frequency. The magnitude of the frequency excursion following a loss of generation may also increase. Amendment of reserve policies or modification of wind turbine inertial response characteristics may be necessary to facilitate increased levels of wind generation. This is particularly true in small isolated power systems.
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High penetration of wind generation will increase the requirement for fast frequency response services as currently wind plants do not provide inertial response. Although the importance of inertia reduction has been widely recognized, its impact on the system scheduling has not been fully investigated. In this context, this paper proposes a novel mixed integer linear programming (MILP) formulation for stochastic unit commitment that optimizes system operation by simultaneously scheduling energy production, standing/spinning reserves and inertia-dependent fast frequency response in light of uncertainties associated with wind production and generation outages. Post-fault dynamic frequency requirements, 1) rate of change of frequency, 2) frequency nadir and 3) quasi-steady-state frequency are formulated as MILP constraints by using the simplified model of system dynamics. Moreover the proposed methodology enables the impact of wind uncertainty on system inertia to be considered. Case studies are carried out on the 2030 Great Britain system to demonstrate the importance of incorporating inertia-dependent fast frequency response in the stochastic scheduling and to indicate the potential for the proposed model to inform reviews of grid codes associated with fast frequency response and future development of inertia-related market.
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It is widely accepted that thermostatically controlled loads (TCLs) can be used to provide regulation reserve to the grid. We first argue that the aggregate flexibility offered by a collection of TCLs can be succinctly modeled as a stochastic battery with dissipation. We next characterize the power limits and energy capacity of this battery model in terms of TCL parameters and random exogenous variables such as ambient temperature and user-specified set-points. We then describe a direct load control architecture for regulation service provision. Here, we use a priority-stack-based control framework to select which TCLs to control at any time. The control objective is for the aggregate power deviation from baseline to track an automatic generation control signal supplied by the system operator. Simulation studies suggest the practical promise of our methods.
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This paper explores methods to coordinate aggregations of thermostatically controlled loads (TCLs; including air conditioners and refrigerators) to manage frequency and energy imbalances in power systems. We focus on opportunities to centrally control loads with high accuracy but low requirements for sensing and communications infrastructure. We compare cases when measured load state information (e.g., power consumption and temperature) is 1) available in real time; 2) available, but not in real time; and 3) not available. We use Markov chain models to describe the temperature state evolution of populations of TCLs, and Kalman filtering for both state and joint parameter/state estimation. A look-ahead proportional controller broadcasts control signals to all TCLs, which always remain in their temperature dead-band. Simulations indicate that it is possible to achieve power tracking RMS errors in the range of 0.26%-9.3% of steady state aggregated power consumption. We also report results in terms of the generator compliance threshold which is commonly used in industry. Results depend upon the information available for system identification, state estimation, and control. Depending upon the performance required, TCLs may not need to provide state information to the central controller in real time or at all.
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The ability of smart meters to control domestic demand during system emergencies was investigated. Direct load control through the smart meters is unlikely to be able to provide primary frequency response because of communication delays. An alternative load control scheme that used a local frequency measurement from the smart meters was investigated. An experimental rig was developed, using commercially available components, to test and demonstrate the load control scheme. The amount of load to be controlled to limit the frequency drop of the Great Britain system to a set of minimum allowable frequencies was found using a simulation program. Operating speeds and the limitations of the components of the load controller in providing primary response are discussed. It is shown that if smart meters are to play any role in primary response then the speed at which the system frequency is measured must be increased very considerably (from around 3 s to 200 ms). This has important implications as the U.K. is now finalizing the specification for more than 20 million smart electricity meters that will be installed by 2020.
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Frequency stability in electricity networks is essential to the maintenance of supply quality and security. This paper investigates whether a degree of built-in frequency stability could be provided by incorporating dynamic demand control into certain consumer appliances. Such devices would monitor system frequency (a universally available indicator of supply-demand imbalance) and switch the appliance on or off accordingly, striking a compromise between the needs of the appliance and the grid. A simplified computer model of a power grid was created incorporating aggregate generator inertia, governor action and load-frequency dependence plus refrigerators with dynamic demand controllers. Simulation modelling studies were carried out to investigate the system's response to a sudden loss of generation, and to fluctuating wind power. The studies indicated a significant delay in frequency-fall and a reduced dependence on rapidly deployable backup generation.
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This paper presents a new mixed-integer linear formulation for the unit commitment problem of thermal units. The formulation proposed requires fewer binary variables and constraints than previously reported models, yielding a significant computational saving. Furthermore, the modeling framework provided by the new formulation allows including a precise description of time-dependent startup costs and intertemporal constraints such as ramping limits and minimum up and down times. A commercially available mixed-integer linear programming algorithm has been applied to efficiently solve the unit commitment problem for practical large-scale cases. Simulation results back these conclusions
Conference Paper
Dynamic load controllers for thermostatically controlled loads should allow for accurate control of power consumption and should not disrupt the quality of service. This paper proposes an intuitive definition of nondisruptiveness for systems with second-order thermal models, based on a decomposition into fast and slow temperature modes. It enables the explicit control of the slow mode temperature using an embedded first order model; control of the fast mode is implicit. Temperature bounds are derived, and the slow mode controller is implemented using an accurate decentralised stochastic control strategy. Simulation results confirm its accuracy and nondisruptiveness.
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This paper studies the modeling and control methods for the provision of ancillary services through aggregating thermostatically controlled appliances (TCAs). A model predictive control (MPC) scheme is presented. Minimum ON/OFF time for protecting the TCA unit is explicitly described in the MPC scheme. A novel method of converting time-integrated interdependent logic conditions, which are for constraining the lockout effect, into inequalities is proposed in this paper. A case study is conducted with realistic data to validate the feasibility of the modeling and control approaches. Parametric studies in terms of temperature deadband width, ambient temperature, and lockout time are conducted to investigate the service quality in different circumstances. The test results reveal that a population of diversified TCAs can become a major source of providing ancillary service. The proposed approach can be specialized to deal with the pure ON/OFF control.
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Active demand response (ADR) is a powerful instrument among electric demand side management strategies to influence the customers’ load shape. Assessing the real potential of ADR programmes in improving the performance of the electric power system is a complex task, due to the strict interaction between supply and demand for electricity, which requires integrated modelling tools. In this paper an analysis is performed aimed at evaluating the benefits of ADR programmes in terms of electricity consumption and operational costs, both from the final user’s and the overall system’s perspective. The demand side technologies considered are electric heating systems (i.e. heat pumps and electric resistance heaters) coupled with thermal energy storage (i.e. the thermal mass of the building envelope and the domestic hot water tank). In particular, the effect of the penetration rate of ADR programmes among consumers with electric heating systems is studied. Results clearly show that increasing the number of participating consumers increases the flexibility of the system and, therefore, reduces the overall operational costs. On the other hand, the benefit per individual participant decreases in the presence of more ADR-adherent consumers since a reduced effort from each consumer is needed. Total cost saving ranges at most between about 400 € and 200 € per participant per year for a 5% and 100% ADR penetration rate respectively.
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There is a remarkable potential for implementing demand response (DR) strategies for several purposes such as peak load reduction, frequency regulation, etc. by using thermostatically-controllable appliances (TCAs). In this study, an end-user comfort violation minimization oriented DR strategy for residential heating, ventilation and air conditioning (HVAC) units is proposed. The proposed approach manipulates the temperature set-point of HVAC thermostats aiming to minimize the average discomfort among end-users enrolled in a DR program, while satisfying the DR event related requirements of the load serving entity. Besides, the fairness for the allocation of the comfort violation among enrolled end-users is also taken into account. Moreover, maintaining the load factor during the contracted DR period compared to a base case in order to reduce the load rebound effect due to shifting the use of HVAC units is also provided with the proposed strategy. Last but not least, the heat index considering the impact of humidity is utilized instead of using ambient dry-bulb temperature through a spatio-temporal forecasting approach.
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The problem of dynamic pricing of electricity in a retail market is considered. A Stackelberg game is used to model interactions between a retailer and its customers; the retailer sets the day-ahead hourly price of electricity and consumers adjust real-time consumptions to maximize individual consumer surplus. For thermostatic demands, the optimal aggregated demand is shown to be an affine function of the day-ahead hourly price. A complete characterization of the trade-offs between consumer surplus and retail profit is obtained. The Pareto front of achievable trade-offs is shown to be concave, and each point on the Pareto front is achieved by an optimal day-ahead hourly price. Effects of integrating renewables and local storage are analyzed. It is shown that benefits of renewable integration all go to the retailer when the capacity of renewable is relatively small. As the capacity increases beyond a certain threshold, the benefit from renewable that goes to consumers increases.
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Power grids have faced major challenges such as increasing consumption, peak demand and CO2 emission. Distributed Generation (DG) as a solution to these issues is affected by source intermittency, grid-side limited storage capabilities and supply/demand mismatch. In order to achieve more benefits and profits for both customers and the utility, integrated demand management techniques can be used. This paper reviews the issues caused by high penetration of renewables in power production, depending on utility characteristics. In addition, several methods in the literature were reviewed and their both single and combined use was investigated with a comparison study in Turkey. In field data based simulations, consumption of refrigerators were scheduled according to the output of a small scale PV system and changes in consumption in a year were calculated. The results were analyzed and compared with each other from the standpoint of change in amount of power taken from grid, number of active operation hours shifted to solar periods, change in annual consumption and achievable savings in electricity bills. In addition to the analysis and comparison of several management methods, the paper also proposes a number of terms that widens applicability and can be used in decision-making processes.
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Collectively, thermostatically controlled loads (TCLs) offer significant potential for short-term demand response. This intrinsic flexibility can be used to provide various ancillary services or to carry out energy arbitrage. This study introduces an aggregate description of the flexibility of a heterogeneous TCL as a leaky storage unit, with associated constraints that are derived from the TCL device parameters and quality of service requirements. In association with a suitable TCL control strategy this enables a straightforward embedding of TCL dynamics in optimisation frameworks. The tools developed are applied to the problem of determining an optimal multi-service portfolio for TCLs. A linear optimisation model is constructed for the optimal simultaneous allocation of frequency services and energy arbitrage. In a case study, optimal service allocations are computed for eight representative classes of cold appliances and the results are validated using simulations of individual refrigerators. Finally, it is demonstrated that clustering of appliances with similar capabilities can significantly enhance the flexibility available to the system.
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Using aggregated heterogeneous thermostatically controlled loads (TCLs) to provide ancillary services in a smart grid is a promising technique. This paper proposes an improved population model with lockout time considered to describe the aggregate dynamics. Based on that, a distributed model predictive control (DMPC) scheme is investigated to control a population of TCLs for the regulation service. Full derivations of the system model and the DMPC scheme are provided. A flexibility penalty is developed and added to the objective function to preserve the regulation flexibility. Simulation results, tested by real data, reveal the feasibility and effectiveness of the proposed method.
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To respond to volatility and congestion in the power grid, demand response (DR) mechanisms allow for shaping the load compared to a base load profile. When tapping on a large population of heterogeneous appliances as a DR resource, the challenge is in modeling the dimensions available for control. Such models need to strike the right balance between accuracy of the model and tractability. The goal of this paper is to provide a medium-grained stochastic hybrid model to represent a population of appliances that belong to two classes: deferrable or thermostatically controlled loads. We preserve quantized information regarding individual load constraints, while discarding information about the identity of appliance owners. The advantages of our proposed population model are 1) it allows us to model and control load in a scalable fashion, useful for ex-ante planning by an aggregator or for real-time load control; 2) it allows for the preservation of the privacy of end-use customers that own submetered or directly controlled appliances.
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This paper focuses on the coordination of a population of thermostatically controlled loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the device bidding and market clearing strategies to motivate self-interested users to realize efficient energy allocation subject to a peak energy constraint. This coordination problem is formulated as a mechanism design problem, and we propose a mechanism to implement the social choice function in dominant strategy equilibrium. The proposed mechanism consists of a novel bidding and clearing strategy that incorporates the internal dynamics of TCLs in the market mechanism design, and we show it can realize the team optimal solution. This paper is divided into two parts. Part I presents a mathematical formulation of the problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.
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Decentralized demand control can help to ensure the balance between electricity demand and supply. In this paper, a multi-agent demand control system is proposed where residential demand is controlled to provide spinning reserves. With the proposed control framework, an aggregator of dynamic demand is able to control the consumption and the response on frequency changes of a cluster of loads. The primary frequency support by the cluster of loads can emulate the primary control of a conventional generator. The total customer welfare remains maximal during the frequency support by applying utility functions for each device.
Article
This letter presents a performance enhancement for a previously developed direct load control scheme that controls (toggles on/off) thermostatically controlled appliances (TCAs) through two-way communication infrastructure for providing load balancing services. In addition to device operating temperature and on/off status (TCA states), two more pieces of information, rates of temperature increase and decrease (RTI/RTD), are calculated at each TCA and communicated to the central controller. By communicating the RTI/RTD to the central controller, the same or even better control performance can be achieved at 2–3 times longer sampling periods, showing significant reduction of the communication needs from each TCA to the central controller.
Article
Thermostatically controlled loads (TCLs), such as refrigerators, air-conditioners and space heaters, offer significant potential for short-term modulation of their aggregate power consumption. This ability can be used in principle to provide frequency response services, but controlling a multitude of devices to provide a measured collective response has proven to be challenging. Many controller implementations struggle to manage simultaneously the short-term response and the long-term payback, whereas others rely on a real-time command-and-control infrastructure to resolve this issue. In this paper, we propose a novel approach to the control of TCLs that allows for accurate modulation of the aggregate power consumption of a large collection of appliances through stochastic control. By construction, the control scheme is well suited for decentralized implementation, and allows each appliance to enforce strict temperature limits. We also present a particular implementation that results in analytically tractable solutions both for the global response and for the device-level control actions. Computer simulations demonstrate the ability of the controller to modulate the power consumption of a population of heterogeneous appliances according to a reference power profile. Finally, envelope constraints are established for the collective demand response flexibility of a heterogeneous set of TCLs.
Article
Residential Thermostatically Controlled Loads (TCLs) such as Air Conditioners (ACs), heat pumps, water heaters and refrigerators have an enormous thermal storage potential for providing regulation reserve to the grid. In this paper, we study the potential resource, regulatory requirements, and economic analysis for TCLs providing frequency regulation service. In particular, we show that the potential resource of TCLs in California is more than enough for both current and predicted near-future regulation requirements for the California power system. Moreover, we estimate the cost and revenue of TCLs, discuss the qualification requirements, recommended policy changes, and participation incentive methods, and compare TCLs with other energy storage technologies. We show that TCLs are potentially more cost-effective than other energy storage technologies such as flywheels, Li-ion, advanced lead acid and Zinc Bromide batteries.
Conference Paper
Federal Energy Regulatory Commission (FERC) Order 755 requires scheduling coordinators to procure and compensate more for regulation resources with faster ramping rates. Thermostatically Controlled Loads (TCLs) are a tremendous demand-side resource for providing fast regulation service due to their population size and their ability of being turned ON or OFF simultaneously. In this paper, we consider modeling and control of a collection of TCLs to provide such regulation service. We first develop a non-uniform bin state transition model for aggregate modeling of a collection of TCLs. The non-uniform model presents a potential for more accurate prediction while requiring fewer number of bins (reducing the complexity of the model) than the existing uniform bin models. We also propose a randomized priority control strategy to manipulate the power consumption of TCLs to track a regulation signal, while preventing short cycling, and reducing wear and tear on the equipment. The proposed control strategy is decentralized in the sense that each TCL makes its own decision solely based on a common broadcast command signal. This framework reduces the communication and computational efforts required for implementing the control strategy. We provide illustrative simulations to show the accuracy of the developed non-uniform model and efficacy of the proposed control strategy.
Article
We investigate the potential for aggregations of residential thermostatically controlled loads (TCLs), such as air conditioners, to arbitrage intraday wholesale electricity market prices via non-disruptive load control. We present two arbitrage approaches: 1) a benchmark that gives us an optimal policy but requires local computation or real-time communication and 2) an alternative based on a thermal energy storage model, which relies on less computation/communication infrastructure, but is suboptimal. We find that the alternative approach achieves around 60%–80% of the optimal wholesale energy cost savings. We use this approach to compute practical upper bounds for savings via arbitrage with air conditioners in California's intraday energy market. We investigate six sites over four years and find that the savings range from 2–37 per TCL per year, and depend upon outdoor temperature statistics and price volatility.
Article
This paper proposes a two-stage robust optimization approach to solve the N- k contingency-constrained unit commitment (CCUC) problem. In our approach, both generator and transmission line contingencies are considered. Compared to the traditional approach using a given set of components as candidates for possible failures, our approach considers all possible component failure scenarios. We consider the objectives of minimizing the total generation cost under the worst-case contingency scenario and/or the total pre-contingency cost. We formulate CCUC as a two-stage robust optimization problem and develop a decomposition framework to enable tractable computation. In our framework, the master problem makes unit commitment decisions and the subproblem discovers the worst-case contingency scenarios. By using linearization techniques and duality theory, we transform the subproblem into a mixed-integer linear program (MILP). The most violated inequalities generated from the subproblem are fed back into the master problem during each iteration. Our approach guarantees a globally optimal solution in a finite number of iterations. In reported computational experiments, we test both primal and dual decomposition approaches. Our computational results verify the effectiveness of our proposed approach.
Article
Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the load population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategy is validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.
Article
In the deregulated power systems setting, the realization of the significant demand flexibility potential should be coupled with its integration in electricity markets. Centralized market mechanisms raise communication, computational and privacy issues while existing dynamic pricing schemes fail to realize the actual value of demand flexibility. In this two-part paper, a novel day-ahead pool market mechanism is proposed, combining the solution optimality of centralized mechanisms with the decentralized demand participation structure of dynamic pricing schemes and based on Lagrangian relaxation (LR) principles. Part I presents the theoretical background, algorithmic approaches and suitable examples to address challenges associated with the application of the mechanism and provides an implementation framework. Non-convexities in reschedulable demand participants' price response and their impacts on the ability of the basic LR structure to reach feasible market clearing solutions are identified and a simple yet effective LR heuristic method is developed to produce both feasible and high quality solutions by limiting the concentrated shift of reschedulable demand to the same low-priced time periods.
Article
This paper presents mathematical optimization models of residential energy hubs which can be readily incorporated into automated decision making technologies in smart grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort level. Novel mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The developed mathematical models result in Mixed Integer Linear Programming (MILP) optimization problems with the objective functions of minimizing energy consumption, total cost of electricity and gas, emissions, peak load, and/or any combination of these objectives, while considering end-user preferences. Several realistic case studies are carried out to examine the performance of the mathematical model, and experimental tests are carried out to find practical procedures to determine the parameters of the model. The application of the proposed model to a real household in Ontario, Canada is presented for various objective functions. The simulation results show that savings of up to 20% on energy costs and 50% on peak demand can be achieved, while maintaining the household owner's desired comfort levels.
Article
Increase of penetration of intermittent renewable power connected to the system will increase the requirements for frequency regulation services. If these services are met by conventional plant running part-loaded, this will not only reduce the system operational efficiency but will also limit the ability of the system to accommodate renewable generation. This work quantifies the value of Dynamic Demand (DD) concept, which enables domestic refrigeration appliances to contribute to primary frequency regulation through an advanced stochastic control algorithm. The benefits of DD providing frequency response are determined for a wide range of future low-carbon generation systems, using an efficient generation scheduling model which includes scheduling of frequency regulation and reserve services. The analysis also considers the potential impact of wind generation on system inertia and primary frequency regulation. Simulations indicate that the benefits of DD increase considerably in systems with high wind penetration, making DD an attractive option for significantly improving system efficiency.
Article
Dynamic demand management is a very promising research direction for improving power system resilience. This paper considers the problem of managing power consumption by means of “smart” thermostatic control of domestic refrigerators. In this approach, the operating temperature of these appliances and thus their energy consumption, is modified dynamically, within a safe range, in response to mains frequency fluctuations. Previous research has highlighted the potential of this idea for responding to sudden power plant outages. However, deterministic control schemes have proved inadequate as individual appliances tend to “synchronize” with each other, leading to unacceptable levels of overshoot in energy demand, when they “recover” their steady-state operating cycles. In this paper we design decentralized random controllers that are able to respond to sudden plant outages and which avoid the instability phenomena associated with other feedback strategies. Stochasticity is used to achieve desynchronization of individual refrigerators while keeping overall power consumption tightly regulated.
Article
Time-domain scheduling simulation is the most effective tool for predicting the operational costs in wind-integrated power systems, because it can represent the inter-temporal constraints that limit the balancing actions of the thermal plant, storage, and demand-side measures. High wind penetrations demand just-in-time commitment decisions that reflect the uncertainties in the wind infeed, so that it is desirable to generate the scheduling decisions using stochastic unit commitment (SUC) with rolling planning. However, the computational burden can make such methods impractical in long simulations. We present an efficient formulation of the SUC problem that is designed for use in scheduling simulations of single-bus power systems. Unlike traditional SUC techniques, the proposed formulation uses a quantile-based scenario tree structure that avoids the need for exogenous operating reserves. We compare the performance of various tree topologies in year-long simulations of a large system. Simple quantile-based trees give statistically significant cost improvements over fixed-quantile deterministic methods and compare favorably with trees based on Monte Carlo-generated scenarios.
Article
This paper proposes a security-constrained forward market clearing algorithm within which the inherent characteristics of demand flexibility are acknowledged when the provision of reserve from the demand side is considered. In the proposed formulation, we co-optimize the cost of scheduling the appropriate resources to guarantee the security of the system and the expected cost of operating under any credible system state. In addition, we consider that consumers can offer to provide spinning reserve capacity deployable by voluntary load reductions in response to contingencies. Due to the load recovery effect (i.e., since energy usage is essentially postponed when demand-side reserve is deployed), in post-contingency states, any voluntary reduction in the load has to be accompanied by a subsequent increase in demand from the initial forecast. We demonstrate that the marginal value of the reserve provided by the demand can only be calculated taking into account the cost of supplying the recovery consumption. Flexible consumers can reduce their payments on average if energy is settled through real-time prices.
System Operability Framework
  • National Grid
National Grid, "System Operability Framework 2015," [Online].
Electricity Ten Years Statement
  • National Grid
National Grid, "Electricity Ten Years Statement," 2014.
Stochastic scheduling with inertiadependent frequency regulation
  • F Teng
  • V Trovato
  • G Strbac
F.Teng, V.Trovato and G.Strbac, "Stochastic scheduling with inertiadependent frequency regulation," IEEE Trans. Power Syst., 2015.
Security and Quality of Supply Standards (SQSS)
  • National Grid
National Grid, "Security and Quality of Supply Standards (SQSS)," [Online]. Available: http://www2.nationalgrid.com/UK/System-Securityand-Quality-of-Supply-Standards/.
Smart Metering Implementation Programme
  • Uk Government
  • Decc
UK Government -DECC, "Smart Metering Implementation Programme," 2014.
Demand Connection Code
  • Entso-E
ENTSO-E, "Demand Connection Code," draft 21 December 2012.