Multi-Objective Control of Residential HVAC Loads for Balancing the User’s Comfort With the Frequency Regulation Performance

Zhang, Di; Li, Canbing; Luo, Shuchen; Luo, Diansheng; Shahidehpour, Mohammad; Chen, Chen; Zhou, Bin

doi:10.1109/tsg.2022.3171847

Cited by 28 publications

(5 citation statements)

References 40 publications

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“…In addition, smart loads can be used in virtual inertia emulators and frequency regulation [13][14][15]. Smart loads, such as noncritical motors [14][15] and inverter air conditioners (IACs) [16][17][18][19][20][21] can be applied for frequency regulation. The contribution of smart loads to the rapid frequency response of the Great Britain transmission system was studied in [13].…”

Section: Introductionmentioning

confidence: 99%

MPC-Based Virtual Energy Storage System Using PV and Air Conditioner to Emulate Virtual Inertia and Frequency Regulation of the Low-Inertia Microgrid

2022

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Grid-connected large-scale power converter-based intermittent renewable energy sources (RES) reduce system inertia, increase frequency fluctuation, and increase the rate of change of frequency (RoCoF). An energy storage system (ESS) is an indispensable component of a smart grid, and is used to overcome low-inertia problems. However, the capital and maintenance costs of ESS are high and high RoCoF events are less frequent in power systems. Therefore, the introduction of a virtual energy storage system (VESS) to provide the function of a conventional ESS for power system ancillary services is an innovative and cost-effective method. This study investigated a VESS using photovoltaic (PV) generators and inverter air conditioners (IACs) to provide virtual inertia and frequency regulation for a low-inertia microgrid. A model predictive control (MPC)-based VESS regulates indoor temperature, microgrid frequency, and RoCoF. The impact of parameter variation, that is, the microgrid frequency weight, indoor temperature weight, virtual inertia gain, and number of IACs, was studied and selected by considering the ability of the parameters to provide virtual inertia and frequency regulation. Finally, the efficiency and robustness of the proposed MPC-based VESS technique are compared with those of a conventional VESS. Simulation results revealed that the proposed MPC-based VESS can improve the virtual inertia, reduce the frequency deviation, and reduce the RoCoF of the studied microgrid. In addition, the proposed method is robust to variations in the system parameters.INDEX TERMS Virtual energy storage system, virtual inertia emulator, load frequency control, inverter air conditioner, photovoltaics generator, microgrid

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Section: Introductionmentioning

confidence: 99%

MPC-Based Virtual Energy Storage System Using PV and Air Conditioner to Emulate Virtual Inertia and Frequency Regulation of the Low-Inertia Microgrid

2022

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“…For HVAC measures, a heating system, cooling system and hot water system are commonly used [39,40]. For the control measures, temperature set-point, HVAC loads and control zone strategies are often studied [41,42].…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

et al. 2023

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Buildings consume large amounts of energy resources and emit considerable amounts of greenhouse gases, especially existing buildings that do not meet energy standards. Building retrofitting is considered one of the most promising and significant solutions to reduce energy consumption and greenhouse gas emissions. However, finding suitable energy efficiency measures for existing buildings is extremely difficult due to the existence of thousands of retrofit measures and the need to meet various objectives. In this paper, a multi-stage decision framework, including a multi-objective optimization model, and a ranking method are proposed to help decision-makers select the optimal energy efficiency measures. The multi-objective optimization model considers the economic and environmental objectives, expressed as the retrofit cost and energy consumption, respectively. The entropy weight ideal point ranking method, an evaluation and ranking method that combines the entropy weight method and ideal point method, is adopted to sort the Pareto front and make a final decision. Then, the proposed decision framework was implemented for the retrofit planning of an educational building in Chongqing, China. The results show that decision-makers can quickly identify near-optimal energy efficiency measures through multi-objective optimization and can select suitable energy efficiency measures using the ranking method. Moreover, energy consumption can be reduced by building retrofitting. The energy consumption of the case building was 64.20 kWh/m2 before retrofitting, and the value can be reduced by 6.79% through retrofitting. Furthermore, the reduction in building energy consumption was significantly improved by applying the decision framework. The highest value of energy consumption was 59.84 kWh/m2, while the lowest value was 27.11 kWh/m2 when implementing the multi-stage decision framework. Thus, this paper provides a useful decision framework for decision-makers to formulate suitable energy efficiency measures.

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“…For HVAC measures, heating system, cooling system and hot water system were commonly used [33,34]. For the control measures, temperature set-point, HVAC loads and control zone strategies were often studied [35,36]. Furthermore, different building types were analysed in recent articles.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A case study of Chongqing

Cui

Hong

Liu

et al. 2022

Preprint

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Buildings consume large amounts of energy resources and emit considerable amounts of greenhouse gas: especially existing buildings which do not meet energy standards. Building retrofitting is considered one of the most promising and significant solutions to reduce energy consumption and greenhouse gas emissions. However, finding suitable energy efficiency measures for existing buildings is extremely difficult due to the existence of thousands of retrofit measures and the need to meet various objectives. In this paper, a multi-stage decision framework including a multi-objective optimization model and a ranking method is proposed to help decision-makers select optimal energy efficiency measures. The multi-objective optimization model takes into account the economic objectives and the environmental objectives, expressed as retrofit cost and energy consumption, respectively. The entropy weight ideal point ranking method is adopted to sort the Pareto front and make a final decision. Then, the proposed decision framework is implemented for the retrofit planning of an educational building in Chongqing, China. The results show that decision-makers can identify near-optimal energy efficiency measures quickly through multi-objective optimization and can select suitable energy efficiency measures by the ranking method. Moreover, energy consumption can be reduced by building retrofitting. The energy consumption of the case building is 64.20 kWh/m2 before retrofitting, and the value can be reduced by 6.79% through retrofitting. Furthermore, the reduction of building energy consumption was significantly improved by applying the decision framework. The highest value of energy consumption is 59.84 kWh/m2, while the lowest value is 27.11 kWh/m2 when implementing the multi-stage decision framework. Thus, this paper provides a useful decision framework for decision-makers to formulate suitable energy efficiency measures.

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Multi-Objective Control of Residential HVAC Loads for Balancing the User’s Comfort With the Frequency Regulation Performance

Cited by 28 publications

References 40 publications

MPC-Based Virtual Energy Storage System Using PV and Air Conditioner to Emulate Virtual Inertia and Frequency Regulation of the Low-Inertia Microgrid

MPC-Based Virtual Energy Storage System Using PV and Air Conditioner to Emulate Virtual Inertia and Frequency Regulation of the Low-Inertia Microgrid

A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

A Multi-stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A case study of Chongqing

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