Trading Cost and Throughput in Geo-Distributed Analytics With A Two Time Scale Approach

Xu, Xinping; Li, Wenxin; Xu, Renhai; Qi, Heng; Li, Keqiu; Zhou, Xiaobo; Chen, Sheng

doi:10.1109/tcc.2020.2994195

Cited by 5 publications

(3 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The two‐timescale Lyapunov optimisation is reported in Ref. [137] in a cost‐throughput tradeoff problem in geo‐distributed data analytics. Without attaining the knowledge of future information, the input data placement and the number of requests to be served are determined in two different timescales.…”

Section: Multi‐timescale Optimisationmentioning

confidence: 99%

Optimisation methods for dispatch and control of energy storage with renewable integration

et al. 2022

View full text Add to dashboard Cite

Renewable energy integration is an effective measure to resolve environmental problems and implement sustainable development, yet the volatility of wind and solar generation has a profound impact on power system operation, calling for sufficient backup capacity. Energy storage can shift demand over time and mitigate real‐time power mismatch and thus help integrate renewable energy resources into power grids. However, the unit capacity price of energy storage is still relatively high, and the capacity of energy storage is usually limited. Given the prominent uncertainty and finite capacity of energy storage, it is crucially important to take full advantage of energy storage units by strategic dispatch and control. From the mathematical point of view, energy storage dispatch and control give rise to a sequential decision‐making process involving uncertain parameters and inter‐temporal constraints. Multitudinous optimisation methods have been developed for such a problem while they differ in two aspects: the modelling of uncertainty and the mechanism to handle uncertainty. This review aims to draw a methodological picture of historical developments and state‐of‐the‐art advances in this research field. These methods are subsumed into three major categories: multistage optimisation, online optimisation, and multi‐timescale optimisation. In addition to introducing the advancements and applications, the authors also explain the motivations and theoretical foundations of these methodologies. The authors hope interested readers can attain a holistic outlook of these sophisticated approaches and choose the most appropriate one for their specific applications.

show abstract

Section: Multi‐timescale Optimisationmentioning

confidence: 99%

Optimisation methods for dispatch and control of energy storage with renewable integration

et al. 2022

View full text Add to dashboard Cite

show abstract

“…(2) Calculate [x (θ), λ (θ), CR] n j by ( 33), (34), and (35). (3) Build new parameter subsets by constraint reversal in (37); save the strictly non-empty ones into Θ n+1 .…”

Section: Algorithm 2 Constructing Explicit Dispatching Policiesmentioning

confidence: 99%

“…The above works employ the conventional Lyapunov optimization with infinite hozizon; the finite-horizon Lyapunov optimization method is first reported in in [31] by M. Dong et al, which introduces an offset term that represents the desired change of SoC level accross the finite time horizon; in recent years, it is used in [32] for joint storage-load scheduling and in [33] for bidirectional storage management in the residential side. Specifically, two-timescale Lyapunov optimization is designed and used for the real-time optimization problems with two different time granularities, such as geo-distributed data analytics [34] and mobile edge computing [35].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Self-Dispatch of a Remote Wind-Storage Integrated Power Plant Without Predictions: Explicit Policy and Performance Guarantee

Guo

Wei

Chen

et al. 2021

IEEE Open J. Power Energy

View full text Add to dashboard Cite

GSelf-MapReduce: A Method for Enhancing Mapreduce Performance in Distributed Heterogeneous Data Centers

Sesen,

Kirisoglu,

Kara

2024

IEEE Access

View full text Add to dashboard Cite

Trading Cost and Throughput in Geo-Distributed Analytics With A Two Time Scale Approach

Cited by 5 publications

References 38 publications

Optimisation methods for dispatch and control of energy storage with renewable integration

Optimisation methods for dispatch and control of energy storage with renewable integration

Real-Time Self-Dispatch of a Remote Wind-Storage Integrated Power Plant Without Predictions: Explicit Policy and Performance Guarantee

GSelf-MapReduce: A Method for Enhancing Mapreduce Performance in Distributed Heterogeneous Data Centers

Contact Info

Product

Resources

About