Three-stage day-ahead scheduling strategy for regional thermostatically controlled load aggregators

Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response.The first stage is on the profit of aggregators and peak load of the grid.The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage,which guarantees the fairness of the regulation and the comfort of users.A single tempera-ture adjustment strategy is used to control TCLs to maximize the response potential in the third stage.Finally,digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within±5%in different situations.In addition,the Gini coefficient of distribu-tion increases by 20%and the predicted percentage of dissatisfied is 48%lower than those without distribution.

Distributed Control of Thermostatically Controlled Loads in Distribution Network with High Penetration of Solar PV

High penetration of solar energy can result in voltage rise in midday,while growth in residential air conditioning is the main contributor of overloading and voltage drop issues during peak demand time.This paper provides a hierarchical control scheme to coordinate multiple groups of aggregated thermostatically controlled loads to regulate network loading and voltage in a distribution network.Considering the limited number of messages that can be exchanged in a realistic communication environment,an event-triggered distributed control strategy is proposed in this paper.Through intermittent on and off toggling of air conditioners,the required active power adjustment is shared among participating aggregators to solve the issue.A case study is conducted and simulation results are presented to demonstrate the performance of the proposed control scheme.

A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

This paper proposes a day-ahead dispatch framework of thermostatically controlled loads(TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a dayahead TCL scheduling model is formulated, which consists of 3 stages: TCL aggregator estimates maximal controllable TCL capacities at each scheduling time interval by solving a optimization model;[ the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator;and ′the TCL aggregator schedules the ON/OFFcontrol actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution(HDDE)algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.

Day-ahead scheduling of large numbers of thermostatically controlled loads based on equivalent energy storage model

Due to their heat/cool storage characteristics, thermostatically controlled loads(TCLs) play an important role in demand response programmers. However, the modeling of the heat/cool storage characteristic of large numbers of TCLs is not simple. In this paper, the heat exchange power is adopted to calculate the power instead of the average power, and the relationship between the heat exchange power and energy storage is considered to develop an equivalent storage model, based on which the time-varying power constraints and the energy storage constraints are developed to establish the overall day-ahead schedulingmodel. Finally, the proposed scheduling method is verified using the simulation results of a six-bus system.

Rolling horizon optimization for real-time operation of thermostatically controlled load aggregator

Thermostatically controlled loads(TCLs)have great potentials to participate in the demand response programs due to their flexibility in storing thermal energy.The two-way communication infrastructure of smart grids provides opportunities for the smart buildings/houses equipped with TCLs to be aggregated in their participation in the electricity markets.This paper focuses on the realtime scheduling of TCL aggregators in the power market using the structure of the Nordic electricity markets a case study.An International Organization of Standardization(ISO)thermal comfort model is employed to well control the occupants’thermal comfort,while a rolling horizon optimization(RHO)strategy is proposed for the TCL aggregator to maximize its profit in the regulation market and to mitigate the impacts of system uncertainties.The simulations are performed by means of a metaheuristic optimization algorithm,i.e.,natural aggregation algorithm(NAA).A series of simulations are conducted to validate the effectiveness of proposed method.

Power Fluctuation Damping of Thermostatically Controlled Loads Based on State Estimation

As a kind of important demand side resource,the thermostatically controlled loads(TCLs)play an important role in the peak load shifting and load balancing programs.This paper establishes a state-queuing(SQ)model for the large-scale TCLs,and estimates the system states based on the Kalman-filtering.Based on state estimation,the control strategy,whose parameters are optimized by the genetic algorithm(GA),is designed to damp the power fluctuation of the TCLs.Finally,the effectiveness of the proposed method is verified.

Unified Control Strategy of Heterogeneous Thermostatically Controlled Loads with Market-based Mechanism

This paper studies the coordination of heterogeneous thermostatically controlled loads(TCLs)to provide the real-time ancillary services.A market-based control framework is adopted for its advantages.The first advantage is that the demand curve-oriented approach makes it possible to form a unified control scheme for heterogeneous loads without identifying their different characteristics.The second one is that the broadcast price signal helps simplify the downlink control and reduce the implementation cost.Then,the separate demand curve construction strategies based on a virtual price for different types of TCLs are presented.The flexibility of each TCL is reflected through the curve,and its practical constraints,i.e.,comfort requirements of users and operation constraints of devices,are satisfied explicitly.To ensure the control fairness and full utilization for the regulation ability of TCL cluster,a comfort-levelequality principle is applied in demand curve construction.Simulations are carried out to verify the effectiveness of the proposed method in providing frequency regulation services,for which a regulation capacity estimation method is developed.Finally,a series of case studies are conducted considering the practical situations,e.g.,model errors,imperfect communication and sudden load change after the end of services.

Ensemble-based uncertainty quantification for coordination and control of thermostatically controlled loads

This work investigates an uncertainty quantification(UQ)framework that analyses the uncertainty involved in modelling control systems to improve control strategy performance.The framework involves solving four problems:identifying uncertain parameters,propagating uncertainty to the quantity of interest,data assimilation and making decisions under quantified uncertainties.A specific group of UQ approaches,known as the ensemble-based methods,are adopted to solve these problems.This UQ framework is applied to coordinating a group of thermostatically controlled loads,which relies on simulating a second-order equivalent thermal parameter model with some uncertain parameters.How this uncertainty affects the prediction and the control of total power is examined.The study shows that uncertainty can be effectively reduced using the measurement of air temperatures.Also,the control objective is achieved fairly accurately with a quantification of the uncertainty.

Review of modeling and control strategy of thermostatically controlled loads for virtual energy storage system

The increasing penetration of renewable energy sources (RESs) brings more power generation fluctuations into power systems, which puts forward higher requirement on the regulation capacities for maintaining the power balance between supply and demand. In addition to traditional generators for providing regulation capacities, the progressed information and communication technologies enable an alternative method by controlling flexible loads, especially thermostatically controlled loads (TCLs) for regulation services. This paper investigates the modeling and control strategies of aggregated TCLs as the virtual energy storage system (VESS) for demand response. First, TCLs are modeled as VESSs and compared with the traditional energy storage system (ESS) to analyze their characteristic differences. Then, the control strategies of VESS are investigated in microgrid and main grid aspects, respectively. It shows that VESS control strategies can play important roles in frequency regulation and voltage regulation for power systems’ stability. Finally, future research directions of VESS are prospected, including the schedulable potential evaluation, modeling of TCLs, hierarchical control strategies of VESS considering ESSs and RESs and reliability and fast response in frequency control for VESS.

Improved Model Predictive Control with Prescribed Performance for Aggregated Thermostatically Controlled Loads

Aggregate thermostatically controlled loads(AT-CLs)are a suitable candidate for power imbalance on demand side to smooth the power fluctuation of renewable energy.A new control scheme based on an improved bilinear aggregate model of ATCLs is investigated to suppress power imbalance.Firstly,the original bilinear aggregate model of ATCLs is extended by the second-order equivalent thermal parameter model to optimize accumulative error over a long time scale.Then,to ensure the control performance of tracking error,an improved model predictive control algorithm is proposed by integrating the Lyapunov function with the error transformation,and theoretical stability of the proposed control algorithm is proven.Finally,the simulation results demonstrate that the accuracy of the improved bilinear aggregate model is enhanced;the proposed control algorithm has faster convergence speed and better tracking accuracy in contrast with the Lyapunov function-based model predictive control without the prescribed performance.

Applications of thermostatically controlled loads for demand response with the proliferation of variable renewable energy

More flexibility is desirable with the proliferation of variable renewable resources for balancing supply and demand in power systems.Thermostatically controlled loads(TCLs)attract tremendous attentions because of their specific thermal inertia capability in demand response(DR)programs.To effectively manage numerous and distributed TCLs,intermediate coordinators,e.g.,aggregators,as a bridge between end users and dispatch operators are required to model and control TCLs for serving the grid.Specifically,intermediate coordinators get the access to fundamental models and response modes of TCLs,make control strategies,and distribute control signals to TCLs according the requirements of dispatch operators.On the other hand,intermediate coordinators also provide dispatch models that characterize the external characteristics of TCLs to dispatch operators for scheduling different resources.In this paper,the bottom-up key technologies of TCLs in DR programs based on the current research have been reviewed and compared,including fundamental models,response modes,control strategies,dispatch models and dispatch strategies of TCLs,as well as challenges and opportunities in future work.

Optimization modeling method for coal-to-electricity heating load considering differential decisions

Heating by electricity rather than coal is considered one effective way to reduce environmental problems. Thus, the electric heating load is growing rapidly, which may cause undesired problems in distribution grids because of the randomness and dispersed integration of the load. However, the electric heating load may also function as an energy storage system with optimal operational control. Therefore, the optimal modeling of electric heating load characteristics, considering its randomness, is important for grid planning and construction. In this study, the heating loads of distributed residential users in a certain area are modeled based on the Fanger thermal comfort equation and the predicted mean vote thermal comfort index calculation method. Different temperatures are considered while modeling the users' heating loads. The heat load demand curve is estimated according to the time-varying equation of interior temperature. A multi-objective optimization model for the electric heating load with heat energy storage is then studied considering the demand response(DR), which optimizes economy and the comfort index. A fuzzy decision method is proposed, considering the factors influencing DR behavior. Finally, the validity of the proposed model is verified by simulations. The results show that the proposed model performs better than the traditional method.

RENEWAL OF BASIC LAWS AND PRINCIPLES FOR POLAR CONTINUUM THEORIES(Ⅸ)—THERMOMECHANICS

The existing fundamental laws of thermodynamics for micropolar continuum field theories are restudied and their incompleteness is pointed out. New first and second fundamental laws for thermostatics and thermodynamics for micropolar continua are postulated. From them all equilibrium equations and the entropy inequality of thermostatics as well as all balance equations and the entropy rate inequalities are naturally and simultaneously deduced. The comparisons between the new results presented here and the corresponding results demonstrated in existing monographs and textbooks concerning micropolar continuum mechanics are made at any time. It should be emphasized to note that, the problem of why the local balance equation of energy and the local entropy inequality could not be obtained from the existing fundamental laws of thermodynamics for micropolar continua, is believed to be clarified.

CMIP5模式对太阳活动准11年周期激发类拉尼娜型海温的评估

利用24个第五次耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)历史试验资料,本文评估了在太阳年代际尺度准11 a周期变化下能否激发出热带太平洋显著的类拉尼娜型海表温度异常的模拟能力。再分析资料分析结果表明,“自下而上”机制解释了在太阳强迫偏强的年份,热带太平洋更容易呈现出显著的类拉尼娜型海温异常。CMIP5模式的评估结果显示,有2/5的模式可以基本再现再分析资料中太阳强迫影响下的热带东太平洋海温负异常,这些模式分为类拉尼娜组;而另有3/5的模式模拟出了相反的信号,分为类厄尔尼诺组。为了进一步探讨CMIP5模式模拟能力不同的原因,本文分析了“自下而上”机制在模式中的表现。“自下而上”机制可分为蒸发过程和海洋恒温(thermostat)过程。结果表明,模式能否模拟出类拉尼娜型海温响应取决于thermostat过程的强弱,其中类拉尼娜组的thermostat过程更强;而蒸发过程没有起到关键作用。

Hybrid versus global thermostatting in molecular-dynamics simulation of methane-hydrate crystallisation

Molecular-dynamics(MD)simulations have been performed for the growth of a spherical methane-hydrate nano-crystallite,surrounded by a supersaturated water–methane liquid phase,using both a hybrid and globalsystem thermostatting approach.It was found that hybrid thermostatting led to more sluggish growth and the establishment of a radial temperature profile about the spherical hydrate crystallite,in which the growing crystal phase is at a higher temperature than the surrounding liquid phase in the interfacial region,owing to latent-heat dissipation.In addition,Onsager’s-hypothesis fluctuation–dissipation analysis of fluctuations in the number of crystal-state water molecules at the interface shows slower growth.

Numerical distortion and effects of thermostat in molecular dynamics simulations of single-walled carbon nanotubes

In this paper, single-walled carbon nanotubes （SWCNTs） are studied through molecular dynamics （MD） simulation. The simulations are performed at temperatures of 1 and 300K separately, with atomic interactions characterized by the second Reactive Empirical Bond Order （REBO） potential, and temperature controlled by a certain thermostat, i.e. by separately using the velocity scaling, the Berendsen scheme, the Nose-Hoover scheme, and the generalized Langevin scheme. Results for a （5,5） SWCNT with a length of 24.5 nm show apparent distortions in nanotube configuration, which can further enter into periodic vibrations, except in simulations using the generalized Langevin thermostat, which is ascribed to periodic boundary conditions used in simulation. The periodic boundary conditions may implicitly be applied in the form of an inconsistent constraint along the axis of the nanotube. The combination of the inconsistent constraint with the cumulative errors in calculation causes the distortions of nanotubes. When the generalized Langevin thermostat is applied, inconsistently distributed errors are dispersed by the random forces, and so the distortions and vibrations disappear. This speculation is confirmed by simulation in the case without periodic boundary conditions, where no apparent distortion and vibration occur. It is also revealed that numerically induced distortions and vibrations occur only in simulation of nanotubes with a small diameter and a large length-to-diameter ratio. When MD simulation is applied to a system with a particular geometry, attention should be paid to avoiding the numerical distortion and the result infidelity.

Deep Unity of Classic and Quantum Physics at the Space Thermostat Presence with Technical Applications

The paper demonstrates deep unity of classic and quantum physics at the space thermostat (ST) presence, which fulfilled all space by the temperature T0 = 2.73 K. The ST presents itself the Cosmic Microwave Background (CMB). From the main quantum position we consider the ST/CMB as the wave function carrier (“quantum background”). The paper is devoted to ST/CMB medium the classic conservation laws of mass, momentum and energy. We show the soliton like solutions of our classic model correspond to Schrodinger’s quantum solutions, demonstrate the atom hydrogen specter and other quantum peculiarities. The paper contains typical technical examples classic/ quantum simulation at the ST presence.

Energy and Buildings

https://www.sciencedirect.com/journal/energy-and-buildings/vol/212/suppl/C Volume 212,1 April 2020(1)Assessment of the impact of HVAC system configuration and control zoning on thermal comfort and energy efficiency in flexible office spaces,by Jasmin Anika Grtner,Francesco Massa Gray,Thomas Auer,Article 109785Abstract:In office buildings,the space layout usually needs to be repeatedly redesigned in order to meet tenants’requirements during the building’s life cycle.In this study,the effect of a flexible space layout design on thermal comfort and energy demand is investigated in a modern open-plan office space.Using dynamic thermal simulation.

A reinforcement learning approach for thermostat setpoint preference learning

Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy systems.While OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints accordingly.Many recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant comfort.These studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat interactions.This paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat overrides.The algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of EnergyPlus.The simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration events.While substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.

Research on cooling-temperature control strategy of fuel-cell engine test bench

As one of the important ways to utilize hydrogen energy,fuel cells are receiving more and more attention and research from countries and institutions.To meet the practical needs of testing the performance of high-power fuel-cell systems and simulate the actual application environment as much as possible,a fuel-cell system test bench is usually used to test the system performance,in which the cooling-temperature control of the test bench has a great impact on the results of the performance of the fuel-cell system.This paper studies the cooling-temperature control strategy of a 150-kW-class fuel-cell engine test platform,proposes a new test-bench cooling-system structure with a thermostat and heat exchanger as the main heat-dissipation components,and compares and analyzes the impact of coordinated thermostat and heat-exchanger control on the fuel-cell system test performance.The test results show that the control strategy of the coordinated operation of a thermostat and heat exchanger can maintain the steady-state error to within±0.3℃and maintain the temperature variation to within±1.5℃during the loading-condition test,so as to avoid the limitation of system output performance due to excessive cooling-temperature fluctuation and ensure that the fuel-cell engine performance-test process is carried out smoothly and efficiently.