Leveraging electrochemical and thermal energy storage systems has been proposed as a strategy to reduce peak power in data centers. Thermal energy storage systems, such as chilled water tanks, have gained increasing attention in data centers for load shifting due to their relatively small capital and operational costs compared to electrochemical energy storage. However, there are few studies investigating the possibility of utilizing thermal energy storage system with resources to provide ancillary services (e.g., frequency regulation) to the grid. This paper proposes a synergistic control strategy for the data center with a chilled water storage providing frequency regulation service by adjusting the chiller capacity, storage charging rate, and IT server CPU frequency. Then, a three-stage multi-market scheduling framework based on a model predictive control scheme is developed to minimize operational costs of data centers participating in both energy and regulation markets. The framework solves a power baseline scheduling problem, a regulation reserve problem, and a real-time power signal tracking problem sequentially. Simulation results show that utilizing the thermal energy storage can increase the regulation capacity bid, reduce energy costs and demand charges, and also harvest frequency regulation revenues. The proposed multi-market scheduling framework in a span of two days can reduce the operational costs up to 8.8% ($1,606.4) compared to the baseline with 0.2% (\$38.7) energy cost reduction, 6.5% (\$1,179.4) from demand reduction, and 2.1% (\$338.3) from regulation revenues.
In this paper, we deal with the power regulation of tethered-wing systems and demonstrate advantages of variable-pitch control in mitigating the dynamic mechanical loads and power fluctuations. The proposed scheme is based on a strategy that maximizes the energy capture during low-speed wind and prevents overloads during the high-speed wind. To realize this strategy, we use a tether reeling-speed controller to track the optimal generator speed during low-speed wind and a MIMO speed-force controller for power limitation during high-speed wind. The controllers are synthesized using H-infinity me…
This work presents a suite of two optimisation models for the short-term scheduling and redispatch of a virtual power plant (VPP) composed of a wind farm and a Li-ion battery, that participates in the day-ahead energy and secondary regulation reserve markets of the Iberian electricity market. First, a two-stage stochastic mixed-integer linear programming model is used to obtain the VPP's generation and reserve schedule and the opportunity cost of the energy stored in the battery. The model has an hourly resolution and a look-ahead period beyond the markets' scheduling horizon and considers the…
Optimizing production scheduling of steel plate hot rolling for economic load dispatch under time-of-use electricity pricing
Xiangtan University（湘潭大学）；Hunan Province Cooperative Innovation Center for Wind Power Equipment and Energy Conversion, College of Information Engineering, Xiangtan University（湘潭大学信息工程学院风力发电设备与能量转换湖南省协同创新中心）；Xiangtan Iron and Steel Corporation Ltd（湘潭钢铁集团有限公司）
Recent years have witnessed a large amount of decentralized data in multiple (edge) devices of end-users, while the aggregation of the decentralized data remains difficult for machine learning jobs due to laws or regulations. Federated Learning (FL) emerges as an effective approach to handling decentralized data without sharing the sensitive raw data, while collaboratively training global machine learning models. The servers in FL need to select (and schedule) devices during the training process. However, the scheduling of devices for multiple jobs with FL remains a critical and open problem. …
The recent decrease in battery manufacturing costs stimulates the market participation of utility-scale battery energy storage systems (BESSs). However, battery degradation remains a major concern for BESS owners while determining their BESS investment and operation strategies. This paper studies the impact of battery degradation on BESS's operation and revenue/cost in real-time energy, reserve, and pay as performance regulation markets. Comparative case studies are performed on two optimization frameworks which model the participation of a price-maker BESS in energy and ancillary services mar…
With the widespread use of distributed energy sources, the advantages of smart buildings over traditional buildings are becoming increasingly obvious. Subsequently, its energy optimal scheduling and multi-objective optimization have become more and more complex and need to be solved urgently. This paper presents a novel method to optimize energy utilization in smart buildings. Firstly, multiple transfer-retention ratio (TRR) parameters are added to the evaluation of distributed renewable energy. Secondly, the normal-boundary intersection (NBI) algorithm is improved by the adaptive weight sum, …
A full-time scale energy management and battery size optimization for off-grid renewable power to hydrogen systems: A battery energy storage-based grid-forming case in Inner Mongolian
