Increasing concern of climate change is driving a push towards clean energy, power systems are undergoing a significant transformation to embrace renewable energy and advanced technologies. Low-voltage power systems (LVPSs) are witnessing a surge in the proliferation of various distributed energy resources, bringing unprecedented opportunities to facilitate renewable energy utilization. Energy storage systems (ESSs) play a key role in LVPSs, enhancing the system stability, operating reliability and flexibility, power quality and cost effectiveness. Therefore, operation and control methods of distributed and grid-scale ESS are to be advanced to address emerging technical challenges in LVPSs, including dynamic operating conditions, local energy markets, uncertainty and computing complexity.
The energy storage system in a form of power, hydrogen or thermal material has been widely used to provide an energy time-shifting function. However, ESSs have potential to provide advanced functions such as power system ancillary services and the flexibility for energy trading. Steady-state charging and discharging operation is effective but sometimes inefficient under the increasingly complicated operating conditions of modern LVPS. Thus, advanced operation and control methods for the distributed and grid-scale ESSs are highly expected to maximize the economic and technical benefits.
On the other hand, the practical factors and issues related to various ESSs and LVPSs should be considered and addressed by new models, frameworks, and algorithms. For example, it is imperative to accurately formulate battery capacity degradation and operating dynamics so that corresponding constraints can be developed and used in the battery scheduling optimization. Emerging operation and control requirements of modern LVPS, including active distribution network, microgrid, smart building, and virtual power plant, on the distributed and grid-scale ESSs are the motivation as well as the objective for researchers to achieve. This topic also leads to interdisciplinary research, involving power system operation and control, integrated energy systems, energy economics, game theory and machine learning.
This Research Topic aims to collect research works in the following topics but not limited to:
- Effective applications of distributed, aggregated, community and grid-scale ESS in modern
LVPSs, with new technical and economic models.
- Advanced operation and control methods of ESS in LVPSs such as active distribution
network, microgrid, smart building, virtual power plant, and integrated energy systems.
- Efficient models of ESS, such as battery, hydrogen, and thermal storage units, considering
capacity degradation, cost effectiveness, dynamics, and coordination with other DERs.
- Advanced algorithms for ESS operation and control, including the optimization method
addressing uncertainty, distributed algorithm, and machine learning application.
- New operation and control frameworks for ESS, including hierarchical coordination,
transactive energy, dynamic aggregation, and capacity sharing/rental.
- Effective power system operation methods with ESS to support ancillary services such as
frequency and voltage control, renewable hosting capacity enhancement, and system
restoration.
Increasing concern of climate change is driving a push towards clean energy, power systems are undergoing a significant transformation to embrace renewable energy and advanced technologies. Low-voltage power systems (LVPSs) are witnessing a surge in the proliferation of various distributed energy resources, bringing unprecedented opportunities to facilitate renewable energy utilization. Energy storage systems (ESSs) play a key role in LVPSs, enhancing the system stability, operating reliability and flexibility, power quality and cost effectiveness. Therefore, operation and control methods of distributed and grid-scale ESS are to be advanced to address emerging technical challenges in LVPSs, including dynamic operating conditions, local energy markets, uncertainty and computing complexity.
The energy storage system in a form of power, hydrogen or thermal material has been widely used to provide an energy time-shifting function. However, ESSs have potential to provide advanced functions such as power system ancillary services and the flexibility for energy trading. Steady-state charging and discharging operation is effective but sometimes inefficient under the increasingly complicated operating conditions of modern LVPS. Thus, advanced operation and control methods for the distributed and grid-scale ESSs are highly expected to maximize the economic and technical benefits.
On the other hand, the practical factors and issues related to various ESSs and LVPSs should be considered and addressed by new models, frameworks, and algorithms. For example, it is imperative to accurately formulate battery capacity degradation and operating dynamics so that corresponding constraints can be developed and used in the battery scheduling optimization. Emerging operation and control requirements of modern LVPS, including active distribution network, microgrid, smart building, and virtual power plant, on the distributed and grid-scale ESSs are the motivation as well as the objective for researchers to achieve. This topic also leads to interdisciplinary research, involving power system operation and control, integrated energy systems, energy economics, game theory and machine learning.
This Research Topic aims to collect research works in the following topics but not limited to:
- Effective applications of distributed, aggregated, community and grid-scale ESS in modern
LVPSs, with new technical and economic models.
- Advanced operation and control methods of ESS in LVPSs such as active distribution
network, microgrid, smart building, virtual power plant, and integrated energy systems.
- Efficient models of ESS, such as battery, hydrogen, and thermal storage units, considering
capacity degradation, cost effectiveness, dynamics, and coordination with other DERs.
- Advanced algorithms for ESS operation and control, including the optimization method
addressing uncertainty, distributed algorithm, and machine learning application.
- New operation and control frameworks for ESS, including hierarchical coordination,
transactive energy, dynamic aggregation, and capacity sharing/rental.
- Effective power system operation methods with ESS to support ancillary services such as
frequency and voltage control, renewable hosting capacity enhancement, and system
restoration.
