Real-Time Energy Management in Microgrids With Reduced Battery Capacity Requirements

Li, Bingcong; Chen, Tianyi; Wang, Xin; Giannakis, Georgios B.

doi:10.1109/tsg.2017.2783894

Cited by 43 publications

(27 citation statements)

References 26 publications

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“…Besides, a theoretical analysis on the tradeoff was not performed in [34]. Compared with the Lyapunov optimization methods used in [29], [30], [32], [33], [35], reinforcement learning methods as applied in [17], [36] can also be used to develop online optimization algorithms. However, reinforcement learning requires the proper development of a function estimator to deal with the continuous states and continuous actions.…”

Section: A Related Work and Motivationsmentioning

confidence: 99%

Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Dong

Hossain

Cheng

et al. 2020

IEEE Trans. Commun.

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User scheduling, beamforming and energy coordination are investigated in smart-grid powered cellular networks (SGPCNs), where the base stations are powered by a smart grid and natural renewable energy sources. Heterogeneous energy coordination is considered in SGPCNs, namely energy merchandizing with the smart grid and energy exchanging among the base stations. A long-term grid-energy expenditure minimization problem with proportional-rate constraints is formulated for SGPCNs. Since user scheduling is coupled with the beamforming vectors, the formulated problem is challenging to handle via standard convex optimization methods. In practice, the beamforming vectors need to be updated over each slot according to the channel variations. User scheduling needs to be updated over several slots (frame) since the frequent scheduling of user equipment can cause reliability issues. Therefore, the Lyapunov optimization method is used to decouple the problem. A practical two-scale algorithm is proposed to schedule users at each frame, and obtain the beamforming vectors and amount of exchanged natural renewable energy at each slot. We prove that the proposed two-scale algorithm can asymptotically achieve the optimal solutions via tuning a control parameter. Numerical results verify the performance of the proposed twoscale algorithm. NOMENCLATURE Variables DefinitionsM Number of BSTs L Number of antennas at each BST N m Number of associated UEs in the mth BST T Number of slots in each frame T k Set of slots in the kth frame h m,n (t k ) Channel-coefficient vector of the (m, n)th access link ω m,n Pathloss of the (m, n)th access link a m,n [k] Scheduled UE indicator y m,n (t k ) Received signal of the (m, n)th UE ).w m,n (t k ) Single-stream beamforming vector for the (m, n)th UE z m,n (t k ) AWGN at the (m, n)th UE σ 2 m,n Power of the AWGN at the (m, n)th UE SINR m,n Received SINR of the (m, n)th UE

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Section: A Related Work and Motivationsmentioning

confidence: 99%

Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Dong

Hossain

Cheng

et al. 2020

IEEE Trans. Commun.

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“…Real-time energy management offers the benefits of being able to detect damaging or potentially dangerous problems as soon as they happen [83][84][85]. It is clear that future microgrid will contain the following new technologies to ensure reliable operation to provide fundamental electrical controllability, a fast inter-converter communication system to coordinate control and operation of potentially hundreds or thousands of electrical sub systems, a high level energy management system to dispatch embedded generation and optimize operation of in-built storage devices.…”

Section: Real-time Energy Managementmentioning

confidence: 99%

Primary and secondary control in DC microgrids: a review

Gao

Kang²,

Cao

et al. 2018

J. Mod. Power Syst. Clean Energy

215

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With the rapid development of power electronics technology, microgrid (MG) concept has been widely accepted in the field of electrical engineering. Due to the advantages of direct current (DC) distribution systems such as reduced losses and easy integration with energy storage resources, DC MGs have drawn increasing attentions nowadays. With the increase of distributed generation, a DC MG consisting of multiple sources is a hot research topic. The challenge in such a multi-source DC MG is to provide voltage support and good power sharing performance. As the control strategy plays an important role in ensuring MG's power quality and efficiency, a comprehensive review of the state-of-art control approaches in DC MGs is necessary. This paper provides an overview of the primary and secondary control methods under the hierarchical control architecture for DC MGs. Specifically, inner loop and droop control approaches in primary control are reviewed. Centralized, distributed, and decentralized approach based secondary control is discussed in details. Key findings and future trends are also presented at last.

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“…However, MPC-based framework can only employ a limited number of time windows ahead to avoid prohibitively high computational complexity with larger predictive window sizes. Some researchers leverage stochastic gradient-based methods to transfer these time-coupling constraints [2], [16]. However, [2] is designed in a centralized manner while [16] only considers coordinating batteries at the transmission level.…”

Section: Introductionmentioning

confidence: 99%

Online Optimization for Networked Distributed Energy Resources With Time-Coupling Constraints

Fan

Zhou

et al. 2021

IEEE Trans. Smart Grid

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This paper proposes a Lyapunov optimization-based online distributed (LOOD) algorithmic framework for active distribution networks with numerous photovoltaic inverters and invert air conditionings (IACs). In the proposed scheme, ADNs can track an active power setpoint reference at the substation in response to transmission-level requests while concurrently minimizing the utility loss and ensuring the security of voltages. In contrast to conventional distributed optimization methods that employ the setpoints for controllable devices only when the algorithm converges, the proposed LOOD can carry out the setpoints immediately relying on the current measurements and operation conditions. Notably, the time-coupling constraints of IACs are decoupled for online implementation with Lyapunov optimization technique. An incentive scheme is tailored to coordinate the customer-owned assets in lieu of the direct control from network operators. Optimality and convergency are characterized analytically. Finally, we corroborate the proposed method on a modified version of 33-node test feeder. Index Terms-Active distribution networks, online distributed optimization, photovoltaic, inverter air conditionings.

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Real-Time Energy Management in Microgrids With Reduced Battery Capacity Requirements

Cited by 43 publications

References 26 publications

Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Cross-Layer Scheduling and Beamforming in Smart-Grid Powered Cellular Networks With Heterogeneous Energy Coordination

Primary and secondary control in DC microgrids: a review

Online Optimization for Networked Distributed Energy Resources With Time-Coupling Constraints

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