State-shift priority based progressive load control of residential HVAC units for frequency regulation

As the penetration of renewable energy continues to increase, stochastic and intermittent generation resources gradually replace the conventional generators, bringing significant challenges in stabilizing power system frequency. Thus, aggregating demand-side resources for frequency regulation attracts attentions from both academia and industry. However, in practice, conventional aggregation approaches suffer from random and uncertain behaviors of the users such as opting out control signals. The risk-averse multi-armed bandit learning approach is adopted to learn the behaviors of the users and a novel aggregation strategy is developed for residential heating, ventilation, and air conditioning (HVAC) to provide reliable secondary frequency regulation. Compared with the conventional approach, the simulation results show that the risk-averse multiarmed bandit learning approach performs better in secondary frequency regulation with fewer users being selected and opting out of the control. Besides, the proposed approach is more robust to random and changing behaviors of the users.

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“…The heat cycle process and power consumption profile of HVAC are depicted in Fig. 1 with cooling mode [21].…”

Section: A Hvac Modelmentioning

confidence: 99%

Residential HVAC Aggregation Based on Risk-averse Multi-armed Bandit Learning for Secondary Frequency Regulation

Chen

Shi

et al. 2020

Journal of Modern Power Systems and Clean Energy

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“…Recent years, a larger number of demand-side users have offered AGC service to power systems. Meanwhile, many AGC strategies have been proposed, enabling different types of demand-side resources to offer frequency regulation service without affecting the users [13][14][15][16][17][18][19][20][21].…”

Section: Demand-side Electric Users Providing Agc Servicementioning

confidence: 99%

“…It allows the loads to follow regulation signals within the expected temperature for comfort. In [14], a progressive load control strategy comes up for residential air conditioners loads implementing primary and secondary frequency regulation efficiently. Proper control strategy has been proven to organize a large population of TCLs for the provision of a frequency reserve in [15].…”

Section: Demand-side Electric Users Providing Agc Servicementioning

confidence: 99%

“…Otherwise, it is unqualified and not allowed to participate in regulation market. Therefore, the regulation performance score of the flow shop should be subject to the inequality as expressed in Formula (14).…”

Section: Regulation Performance Scorementioning

confidence: 99%

“…Figure 2 shows the relationship between the scheduling optimization and bidding optimization of a flow shop. First, the flow shop is required to solve bidding strategy according to Formulas (7)- (14) and (22). However, the coefficients of the Formula (22) come from linear regression fitting, whose sampled-data partly derives from the solution of the flow shop scheduling optimization, as expressed by the Link Line 1 in Figure 2.…”

Section: Numerical Settingmentioning

confidence: 99%

See 2 more Smart Citations

Flow Shop Providing Frequency Regulation Service in Electricity Market

Wang

Pei

et al. 2020

Energies

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Electricity cost is one of main production costs for flow shops. Providing frequency regulation services can help electric loads reduce their electricity costs. Previous studies mostly focus on automatic generation control (AGC) strategies for other types of electric loads, such as air conditioners, EVs or battery storage. In this paper, we find flow shops competent to follow regulation signals and avoid interrupts of processing with the help of scheduling optimization. This finding may be an aid for flow shops by availing regulation services to the market and making a profit. Hence, we propose an AGC strategy for optimizing flow shop scheduling, without affecting the operation. To formulate the bidding strategy for flow shops in regulation market, we considered as many relevant factors as possible, including the regulation performance and yield of flow shops, constraints on load power, regulation reserve capacity and machines operation, inventory of each semi-finished product, AGC strategy-as well as the coupling between the bids in both energy market and regulation market. Our case study shows the potential of the methodology proposed in this paper to cut down the electric cost of flow shops and supplies of performance-qualified frequency regulation service.

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Energy priority control strategy and reward allocation mechanism for thermostatically controlled loads based on leaky storage model

Yang

Li²,

Ma³

et al. 2022

Electric Power Systems Research

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State-shift priority based progressive load control of residential HVAC units for frequency regulation

Cited by 15 publications

References 37 publications

Residential HVAC Aggregation Based on Risk-averse Multi-armed Bandit Learning for Secondary Frequency Regulation

Residential HVAC Aggregation Based on Risk-averse Multi-armed Bandit Learning for Secondary Frequency Regulation

Flow Shop Providing Frequency Regulation Service in Electricity Market

Energy priority control strategy and reward allocation mechanism for thermostatically controlled loads based on leaky storage model

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