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

Journal of Modern Power Systems and Clean Energy 2017年第6期5卷 947-958页

作者： Fengji LUO Gianluca RANZI Zhaoyang DONG School of Civil Engineering University of SydneySydneyAustralia State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina School of Electrical and Information Engineering University of SydneySydneyAustralia

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.

关键词： thermostatically controlled load Demand side management Rolling horizon optimization Thermal comfort model Demand response

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Improved Model Predictive Control with Prescribed Performance for Aggregated thermostatically controlled loads

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 430-439页

作者： Yang Yu Li Quan Zengqiang Mi Jianbin Lu Shengqiang Chang Yubao Yuan the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBaodingChina the Innovation Center for Hebei Intelligent Grid Distribution Technology Shijiazhuang Kelin Electric Co.Ltd.ShijiazhuangChina

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.

关键词： Lyapunov function model predictive control power tracking prescribed performance thermostatically controlled load

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

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Frontiers in Energy 2022年第1期16卷 64-73页

作者： Meng SONG Wei SUN Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment Southeast UniversityNanjing 210096China Department of Electrical and Computer Engineering University of Central FloridaOrlandoFL 32816USA

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.

关键词： thermostatically controlled load demand response renewable energy power system operation

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Probabilistic Assessment of Impact of Flexible loads Under Network Tariffs in Low-voltage Distribution Networks

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Journal of Modern Power Systems and Clean Energy 2021年第4期9卷 951-962页

作者： Donald Azuatalam Archie C.Chapman Gregor Verbic School of Electrical and Information Engineering The University of SydneySydneyNew South WalesAustralia

Given the historically static nature of low-voltage networks, distribution network companies do not possess the tools for dealing with an increasingly variable demand due to the high penetration of distributed energy resources (DERs). Within this context, this paper proposes a probabilistic framework for tariff design that minimises the impact of DER on network performance, stabilises the revenue of network company, and improves the equity of network cost allocation. To deal with the lack of customers’ response, we also show how DER-specific tariffs can be complemented with an automated home energy management system (HEMS) that reduces peak demand while retaining the desired comfort level. The proposed framework comprises a nonparametric Bayesian model which statistically generates synthetic load and PV traces, a hot-water-use statistical model, a novel HEMS to schedule customers’ controllable devices, and a probabilistic power flow model. Test cases using both energy- and demand-based network tariffs show that flat tariffs with a peak demand component reduce the customers’ cost, and alleviate network constraints. This demonstrates, firstly, the efficacy of the proposed tool for the development of tariffs that are beneficial for the networks with a high penetration of DERs, and secondly, how customers’ HEM systems can be part of the solution.

关键词： Battery energy storage system demand-based tariff distributed energy resource(DER) home energy management system(HEMS) low-voltage network solar photovoltaic(PV) thermostatically controlled load

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