Exploring the Cellular Base Station Dispatch Potential Towards Power System Frequency Regulation

Yong, Pei; Zhang, Ning; Liu, Yuxiao; Hou, Qingchun; Li, Yaowang; Chen, Kang

doi:10.1109/tpwrs.2021.3124141

Cited by 26 publications

(8 citation statements)

References 12 publications

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“…Typically, most of 5G BSs are constructed with BSBBs for a backup duration of 3 hours to meet the reliability requirements for power supply [15]. Thus, the minimum backup energy demand of BSBB k at time instant t can be calculated:…”

Section: A Evaluating Dispatchable Capacity Of Bsbbsmentioning

confidence: 99%

“…Reference [14] further investigates the potential of the spare capacity of BSBB in stabilizing the photovoltaic (PV) output in 5G BS microgrids. Besides, a rule-based mechanism is constructed to coordinate the spare capacity of massive distributed BSBB to provide secondary frequency regulation service [15]. Reference [16] considers 5G BSBBs as a new flexible resource and uses them to optimize the voltage profile of active distribution networks.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Stochastic Scheduling of Massive Backup Batteries in Cellular Networks for Operational Reserve and Frequency Support Ancillary Services

Li,

Fang,

et al. 2024

Journal of Modern Power Systems and Clean Energy

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Base station (BS) backup batteries (BSBBs), with their dispatchable capacity, are potential demand-side resources for future power systems. To enhance the power supply reliability and post-contingency frequency security of power systems, we propose a two-stage stochastic unit commitment (UC) model incorporating operational reserve and post-contingency frequency support provisions from massive BSBBs in cellular networks, in which the minimum backup energy demand is considered to ensure BS power supply reliability. The energy, operational reserve, and frequency support ancillary services are co-optimized to handle the power balance and post-contingency frequency security in both forecasted and stochastic variable renewable energy (VRE) scenarios. Furthermore, we propose a dedicated and scalable distributed optimization framework to enable autonomous optimizations for both dispatching center (DC) and BSBBs. The BS model parameters are stored and processed locally, while only the values of BS decision variables are required to upload to DC under the proposed distributed optimization framework, which safeguards BS privacy effectively.Case studies on a modified IEEE 14-bus system demonstrate the effectiveness of the proposed method in promoting VRE accommodation, ensuring post-contingency frequency security, enhancing operational economics, and fully utilizing BSBBs' energy and power capacity. Besides, the proposed distributed optimization framework has been validated to converge to a feasible solution with near-optimal performance within limited iterations. Additionally, numerical results on the Guangdong 500 kV provincial power system in China verify the scalability and practicality of the proposed distributed optimization framework.

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Section: A Evaluating Dispatchable Capacity Of Bsbbsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Stochastic Scheduling of Massive Backup Batteries in Cellular Networks for Operational Reserve and Frequency Support Ancillary Services

Li,

Fang,

et al. 2024

Journal of Modern Power Systems and Clean Energy

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“…In terms of economy, the LCC, return on investment and initial investment are used as standards. The calculation of LCC is shown in the following [14]:…”

Section: Economic Modelmentioning

confidence: 99%

“…The purpose of energy conservation is achieved by adjusting the operating status of base stations [5,6] and even shutting down some base stations according to actual user needs [7][8][9]. Furthermore, references [13,14] propose the integration of partial backup energy storage in base stations into grid dispatch, resulting in increased economic benefits of base stations and improved stability of the distribution network. However, on one hand, optimization of base station operating modes have limited ability to reduce energy demands.…”

Section: Introductionmentioning

confidence: 99%

Improved Model of Base Station Power System for the Optimal Capacity Planning of Photovoltaic and Energy Storage System

Zhu,

Wang,

Guo

et al. 2023

Electronics

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The widespread installation of 5G base stations has caused a notable surge in energy consumption, and a situation that conflicts with the aim of attaining carbon neutrality. Numerous studies have affirmed that the incorporation of distributed photovoltaic (PV) and energy storage systems (ESS) is an effective measure to reduce energy consumption from the utility grid. The optimization of PV and ESS setup according to local conditions has a direct impact on the economic and ecological benefits of the base station power system. An improved base station power system model is proposed in this paper, which takes into consideration the behavior of converters. And through this, a multi-faceted assessment criterion that considers both economic and ecological factors is established. Then, the PV and ESS capacity optimization for base stations under multiple scenarios is realized. The case study indicates that the optimization process of PV and ESS is significantly influenced by the behavior of the converter.

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“…Literature [4] considers the dual uncertainties of battery swap stations and photovoltaic power generation, and proposes a day-ahead economic dispatch method for electric vehicle battery swap stations based on chance constrained programming and probability sequence operations, which effectively reduces operating costs. Literature [5] points out the impact of base station energy storage scheduling on power system frequency regulation, estimates the feasible scheduling boundary for each base station to participate in frequency regulation, and then proposes a framework to coordinate BSs to provide frequency support. By introducing large-scale distributed base stations, improved frequency performance of power systems.…”

Section: Introductionmentioning

confidence: 99%

Optimization strategy of base station energy consumption based on predictive control

Liu,

Wang,

Wang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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This article focuses on the optimized operation of communication base stations, especially the effective utilization of energy storage batteries. Currently, base station energy storage batteries are often idle and do not participate in power supply, resulting in resource waste and battery life issues. Therefore, this paper uses the charge and discharge control of energy storage batteries, combined with wind and solar resources and time-of-use electricity prices, to achieve "peak shaving and valley filling" of base station load power and significantly reduce operating costs. The article proposes an optimal dispatch model from two stages: day-ahead and intra-day. By calculating the base station load and wind and solar forecast, the day-ahead economic operation strategy is derived, and the intra-day dispatch plan is continuously adjusted according to the actual situation. Through numerical example analysis, the effectiveness of the method proposed in this article is verified.

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Exploring the Cellular Base Station Dispatch Potential Towards Power System Frequency Regulation

Cited by 26 publications

References 12 publications

Distributed Stochastic Scheduling of Massive Backup Batteries in Cellular Networks for Operational Reserve and Frequency Support Ancillary Services

Distributed Stochastic Scheduling of Massive Backup Batteries in Cellular Networks for Operational Reserve and Frequency Support Ancillary Services

Improved Model of Base Station Power System for the Optimal Capacity Planning of Photovoltaic and Energy Storage System

Optimization strategy of base station energy consumption based on predictive control

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