Comparative analysis on operation strategies of CCHP system with cool thermal storage for a data center

Xu, Song; Liu, Liuchen; Zhu, Tong; Zhang, Tao; Zhu, Wu

doi:10.1016/j.applthermaleng.2016.07.142

Cited by 55 publications

(8 citation statements)

References 19 publications

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“…CHP output power following the thermal load (FTL) [30], as shown in Equation ( 3). In the FTL mode, the CHP operating power follows the change of the thermal load, giving priority to ensuring the reliable energy supply of the thermal load.…”

Section: Chpmentioning

confidence: 99%

Capacity configuration optimization of standalone multi‐energy hub considering electricity, heat and hydrogen uncertainty

Hou

Liu

Xiao

et al. 2021

Energy Conversion and Econom

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Standalone multi-energy hub is the next frontier of electric grid modernization. It is vital to optimize the standalone multi-energy hub capacity configuration to enhance the hub reliability, economic efficiency, and sustainability. Therefore, this paper proposes a novel multi-objective capacity configuration model for standalone multi-energy hub considering electricity, heat and hydrogen energy uncertainty. First, the standalone multi-energy hub model with electricity, heat, and hydrogen energy is established. It takes into account photovoltaic generators, wind generation, combined heat and power units, power to gas, gas boiler and hydrogen storage tank to meet the electrical, thermal and hydrogen energy demands. At the same time, in order to solve the influence of uncertainty on hub capacity configuration, the typical source-load scenarios are established considering the uncertainty of wind speed, solar radiation and energy demands. On this basis, the objective functions and constraints of the capacity configuration model are presented. The improved hybrid multi-objective particle swarm optimization algorithm and fuzzy membership function are used to solve the model. Finally, case studies verified the effectiveness and rationality of the proposed model.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Chpmentioning

confidence: 99%

Capacity configuration optimization of standalone multi‐energy hub considering electricity, heat and hydrogen uncertainty

Hou

Liu

Xiao

et al. 2021

Energy Conversion and Econom

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show abstract

“…The market size of Internet Data Centers (IDCs) in China and the world is shown in Figure 1 [1], reflecting a clear trend of rapid increase in recent years (average rate of increase is 40% in China). Along with this rapid development, high energy consumption and carbon emissions have become a major problem for IDCs [2]. The existing research [3] shows that the reasonable configuration of data-center-park-integrated energy systems (DCP-IES) can realize economical, low-carbon, and reliable operation.…”

Section: Dcp-iess and Their Key Characteristicsmentioning

confidence: 99%

Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations

Liu

et al. 2020

Energies

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The analysis of energy configuration in the planning of data-center-park-integrated energy systems (DCP-IESs) has become an enormous challenge, owing to multi-energy complementarity, energy cascade use, and energy security. In this study, a configuration model of DCP-IESs was established to obtain the economic and low-carbon energy uses of the data centers, based on mixed integer linear programming. In the model, carbon emissions were converted to economic indicators through carbon pricing. Then, the configuration model was modified according to the security of the proposed device switching logic, and the Markov-based reliability estimation method was used to ensure the redundant design of the configuration. Using the new energy configuration method, the DCP-IES configuration scheme could be obtained under economical, low-carbon, and high reliability conditions. A data center park in Shanghai was selected as a case study, and the results are as follows: it will only take 2.88 years for the economics of DCP-IES to reach those of traditional data center energy systems. Additionally, the use of configuration model in DCP-IES would result in a reduction in annual carbon emissions of 39,323 tons, with a power usage effectiveness of 1.388, whereas an increase in reliability results in an increasingly faster increase in the initial investment cost.

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“…It is verified that operation optimization can improve their performance to some extent [7][8][9][10]. However, fluctuating energy demands might not always fall within the high efficiency region of CCHP systems [11,12]. Satisfactory operation cannot be achieved easily without energy storage units, which can facilitate high-efficiency CCHP system operation and increase the energy conservation rate by approximately 21% [13].…”

Section: Introductionmentioning

confidence: 97%

Dynamic Optimization of Combined Cooling, Heating, and Power Systems with Energy Storage Units

Kuang

Zhang

et al. 2018

Energies

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In this paper, a combined cooling, heating, and power (CCHP) system with thermal storage tanks is introduced. Considering the plants’ off-design performance, an efficient methodology is introduced to determine the most economical operation schedule. The complex CCHP system’s state transition equation is extracted by selecting the stored cooling and heating energy as the discretized state variables. Referring to the concept of variable cost and constant cost, repeated computations are saved in phase operating cost calculations. Therefore, the most economical operation schedule is obtained by employing a dynamic solving framework in an extremely short time. The simulation results indicated that the optimized operating cost is reduced by 40.8% compared to the traditional energy supply system.

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Comparative analysis on operation strategies of CCHP system with cool thermal storage for a data center

Cited by 55 publications

References 19 publications

Capacity configuration optimization of standalone multi‐energy hub considering electricity, heat and hydrogen uncertainty

Capacity configuration optimization of standalone multi‐energy hub considering electricity, heat and hydrogen uncertainty

Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations

Dynamic Optimization of Combined Cooling, Heating, and Power Systems with Energy Storage Units

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