Coordination optimization of multiple thermostatically controlled load groups in distribution network with renewable energy

Wei, Congying; Xu, Jian; Liao, Siyang; Sun, Yuanzhang; Jiang, Yibo; Zhang, Zhen

doi:10.1016/j.apenergy.2018.09.105

Cited by 28 publications

(8 citation statements)

References 33 publications

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“…The power consumption of TCLs can be easily controlled by changing set point temperature with a short time, making it suitable to provide operating reserve by reducing power consumption according to the reserve deployment instructions [33], [34]. Considering that the power consumption of an individual TCL is too small, TCLs are usually aggregated as an equivalent operating reserve provider (ORT) to provide operating reserve to the power system [35], [36]. Then, the system operator can dispatch the TCLs as the traditional operating reserve to enhance the reliability of the power systems [37].…”

Section: Framework To Obtain the Multi-state Model Of Operating Resermentioning

confidence: 99%

Multi-state operating reserve model of aggregate thermostatically-controlled-loads for power system short-term reliability evaluation

et al. 2019

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

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Section: Framework To Obtain the Multi-state Model Of Operating Resermentioning

confidence: 99%

Multi-state operating reserve model of aggregate thermostatically-controlled-loads for power system short-term reliability evaluation

et al. 2019

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“…. , n. Based on previous research [6,8,9], we use the following continuous time equation to describe their dynamics:…”

Section: Thermostatically Controlled Loadsmentioning

confidence: 99%

“…In addition, as the residential TCLs are generally constructed in a large quantity with relatively small capacity in practice, it can be complicated and inefficient for the microgrid operator to control each TCL directly. Therefore, the aggregation model of distributed TCLs is used in many studies [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Authors of [8] propose a two-stage optimization model for a group of TCLs to smooth the power fluctuation resulting from PV systems in distribution networks. In the first stage, the regulation capability of TCL groups is determined from the aggregation of user inputs including the change in the temperature set points and maximum allowed temperature, which is then used to calculate the required regulation power to smooth the net exchange power fluctuation at a minimum cost.…”

Section: Introductionmentioning

confidence: 99%

“…Since predicted data on renewable power, electricity price and load demand are used in their algorithms, one of the main challenges in these studies can be the errors in forecasting. To address this, the receding horizon approach is utilized in most studies [8][9][10][11][12][13][14][15], as uncertainties can be reduced to a relatively low level with constantly updated forecasting data. Nevertheless, this approach has a strict requirement for the computation time as the set of results over a forecasting horizon should be solved before the first control step over the horizon expires.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads

2019

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Constructing microgrids with renewable energy systems could be one feasible solution to increase the penetration of renewable energy. With proper control of the battery energy storage system (BESS) and thermostatically controlled loads (TCLs) in such microgrids, the variable and intermittent energy can be smoothed and utilized without the interference of the main power grid. In this paper, a decentralized control strategy for a microgrid consisting of a distributed generator (DG), a battery energy storage system, a solar photovoltaic (PV) system and thermostatically controlled loads is proposed. The control objective is to maintain the desired temperature in local buildings at a minimum cost. Decentralized control algorithm involving variable structure controller and dynamic programming is used to determine suitable control inputs of the distributed generator and the battery energy storage system. The model predictive control approach is utilized for long-term operation with predicted data on solar power and outdoor temperature updated at each control step.

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Optimal placement of phasor measurement unit in distribution networks considering the changes in topology

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et al. 2019

Applied Energy

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Coordination optimization of multiple thermostatically controlled load groups in distribution network with renewable energy

Cited by 28 publications

References 33 publications

Multi-state operating reserve model of aggregate thermostatically-controlled-loads for power system short-term reliability evaluation

Multi-state operating reserve model of aggregate thermostatically-controlled-loads for power system short-term reliability evaluation

Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads

Optimal placement of phasor measurement unit in distribution networks considering the changes in topology

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