A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response

Ju, Liu; Lu, Xiaolong; Yang, Shenbo; Li, Gen; Fan, Wei; Pan, Yushu; Qiao, Huiting

doi:10.1016/j.apenergy.2022.120155

Cited by 28 publications

(11 citation statements)

References 27 publications

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“…[20] The RO model utilizes the uncertainty sets to characterize the continuous range of uncertain values and implement optimization under the "worst-case" scenario in the set. [21] However, the "worst-case" scenario is less likely to occur, which makes the RO model too conservative to achieve the desirable optimization effect. [22,23] In addition to the worst-case RO discussed, robust design optimization (RDO) considers probabilistic uncertainties at the model inputs and optimizes both the expected performance and the variability of that performance.…”

Section: Literature Surveymentioning

confidence: 99%

“…s.t. Equation ( 20), (21), and ( 22), ( 25) By obtaining Equation ( 20)-( 22), Equation ( 25) and ( 26), the aforementioned problems of min{sup} double-layer structure, and infinite dimensional variable f are solved effectively.…”

Section: Model Reformulationmentioning

confidence: 99%

“…[ 20 ] The RO model utilizes the uncertainty sets to characterize the continuous range of uncertain values and implement optimization under the “worst‐case” scenario in the set. [ 21 ] However, the “worst‐case” scenario is less likely to occur, which makes the RO model too conservative to achieve the desirable optimization effect. [ 22,23 ]…”

Section: Introductionmentioning

confidence: 99%

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Temporal Covariance‐Involved Distributionally Robust Optimization for Photovoltaic–Hydrogen Integrated Energy System Scheduling Considering Source, Load Sides, and Market Uncertainties

Wang,

Jia,

Song

et al. 2024

Energy Tech

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Under the pressures of environmental pollution, solar energy and hydrogen have attracted widespread attention, thus promoting the development of photovoltaic–hydrogen integrated energy system. However, multiple uncertainties seriously interfere with the system's economic and stable operation. Therefore, this article proposes a temporal covariance‐involved distributionally robust optimization model for system scheduling considering multiple uncertainties from source, load sides, and market. First, the possible range of the uncertainties distribution is described by a novel moment‐based ambiguity set modified with temporal covariances. Second, the objective function is constructed as a min{sup} form to minimize the expected operation cost under the “worst‐case” distribution in the ambiguity set. Then, the constraints present a two‐stage structure. The first stage guarantees the operation feasibility under the forecasting scenario, and the second stage accounts for forecasting errors to formulate the rescheduling space for resisting uncertainties. Finally, the model is transformed into an easy‐to‐solve semidefinite programming. Simulation finds that the model 1) significantly reduces the average and standard deviation of system operation cost by 22.35% and 27.41%, respectively; 2) ensures 100% photovoltaic accommodation; and 3) maintains low conservativeness and complexity simultaneously. Above all, this study provides an effective approach for comprehensive ultilization of clean energies under multiple uncertainties.

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Section: Literature Surveymentioning

confidence: 99%

Section: Model Reformulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Temporal Covariance‐Involved Distributionally Robust Optimization for Photovoltaic–Hydrogen Integrated Energy System Scheduling Considering Source, Load Sides, and Market Uncertainties

Wang,

Jia,

Song

et al. 2024

Energy Tech

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“…Thus, the large-scale application and promotion of the system depends on the support of policies. Ju et al [29] developed a rural integrated energy system to convert straw, garbage, and other rural biomass waste resources to energy. The system structure of biogas-based rural energy system is shown in Figure 4.…”

Section: Grid-connected Energy Systemmentioning

confidence: 99%

Rural Integrated Energy System Based on Bibliometric Analysis: A Review of Recent Progress

Yu,

Li,

Liu

2024

Processes

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In rural areas with higher agricultural energy consumption, ensuring low-carbon transformation and rapid penetration is crucial; therefore, the importance of rural energy system in energy transformation is even more prominent. In order to better understand the research progress of rural integrated energy system, the existing structure of rural energy system and design method are briefly introduced, and the bibliometric method is applied to analyze publications from 2013 to 2023. Based on the Scopus database, 915 publications have been retrieved. These publications are analyzed from the perspective of citation, author, address, and published journal. It is concluded that existing researches mostly use conventional energy technologies to achieve power supply in rural areas, lacking analysis of the potential application of emerging energy technologies and research on multi-energy demand. Furthermore, the review reveals the economy of grid-connected rural energy system is mainly related to geographical location, system configuration, and resource endowment. The bibliometric analysis indicated that these publications are mainly from India and China; the average citation is 24.98, and each article is co-published by 3.66 authors, 2.26 institutes, and 1.46 countries. This work is helpful for scholars to understand the research status on the rural integrated energy system.

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“…[3] presented a coupled multi‐carrier energy supply framework for biogas‐solar‐wind hybrid renewable systems, and Ref. [13] designed a micro‐energy network based on rural biomass waste energy conversion systems (BWs). In the context of community‐integrated energy systems (CIES), Ref.…”

Section: Introductionmentioning

confidence: 99%

Multi‐scale coordinated optimal dispatch method of electricity‐thermal‐hydrogen integrated energy systems

Zheng

Xiao

Liu

et al. 2023

IET Energy Syst Integration

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To achieve carbon neutrality, renewable energy‐based power systems and hydrogen are increasingly being promoted. A novel electricity‐thermal‐hydrogen integrated energy system that combines new energy generation, multi‐source load, and multiple energy storage is proposed by the authors. To address uncertainties in new energy output, and issues of untimely unit regulation response and large planning tracking errors, a multi‐scale scheduling method based on model predictive control (MPC) was proposed. In the day‐ahead dispatching stage, an optimal economic dispatching model was established with the lowest system operation cost as the optimisation objective. The model considers equipment investment, operation, maintenance, and peak‐to‐valley differences in electricity prices. In the intraday dispatching stage, an MPC‐based intraday rolling optimisation correction strategy was proposed to cope with contact line power fluctuations caused by prediction errors of new energy and multi‐source load. This strategy combines time‐domain rolling and feedback correction of the real‐time system state to eliminate the influence of uncertainty factors in the microgrid. The MPC‐based intraday rolling optimal scheduling model was established in the form of a discrete state space and transformed into a quadratic planning problem to improve the efficiency and accuracy of the model solution. Finally, a typical microgrid was used as an example to verify the effectiveness of the proposed method. Results show that the contact line tracking error can be within 0.025 kW, and the single scheduling time was within 0.14 s.

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A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response

Cited by 28 publications

References 27 publications

Temporal Covariance‐Involved Distributionally Robust Optimization for Photovoltaic–Hydrogen Integrated Energy System Scheduling Considering Source, Load Sides, and Market Uncertainties

Temporal Covariance‐Involved Distributionally Robust Optimization for Photovoltaic–Hydrogen Integrated Energy System Scheduling Considering Source, Load Sides, and Market Uncertainties

Rural Integrated Energy System Based on Bibliometric Analysis: A Review of Recent Progress

Multi‐scale coordinated optimal dispatch method of electricity‐thermal‐hydrogen integrated energy systems

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