Energy Pricing and Sharing Strategy Based on Hybrid Stochastic Robust Game Approach for a Virtual Energy Station With Energy Cells

Yin, Shuangrui; Ai, Qian; Li, Jiamei; Li, Zhaoyu; Fan, Songli

doi:10.1109/tste.2020.3019494

Cited by 31 publications

(6 citation statements)

References 34 publications

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“…Generally, the papers in this category have used iterative methods of column and constraint generation (C&CG) algorithm or Benders decomposition. Articles [89], [101], [107], [109], [112], [113], [126] have used ARO to handle the binary variables stemming from the start-up and shut-down generator constraints in the economic dispatch and unit commitment problem. Regarding uncertainty, [109] copes with the uncertainty of wind power generation, while [101] has taken into account both renewable energy and price uncertainties.…”

Section: ) Adaptive Robust Optimizationmentioning

confidence: 99%

“…Articles [89], [101], [107], [109], [112], [113], [126] have used ARO to handle the binary variables stemming from the start-up and shut-down generator constraints in the economic dispatch and unit commitment problem. Regarding uncertainty, [109] copes with the uncertainty of wind power generation, while [101] has taken into account both renewable energy and price uncertainties. The unit commitment constraints have led the authors in [82] to use ARO in the presence of uncertainties of wind power, loads and electricity prices, where all the uncertainties have been addressed by one interval of deviation.…”

Section: ) Adaptive Robust Optimizationmentioning

confidence: 99%

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Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

et al. 2023

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Co-designing energy systems across multiple energy carriers is increasingly attracting attention of researchers and policy makers, since it is a prominent means of increasing the overall efficiency of the energy sector. Special attention is attributed to the so-called energy hubs, i.e., clusters of energy communities featuring electricity, gas, heat, hydrogen, and also water generation and consumption facilities. Managing an energy hub entails dealing with multiple sources of uncertainty, such as renewable generation, energy demands, wholesale market prices, etc. Such uncertainties call for sophisticated decision-making techniques, with mathematical optimization being the predominant family of decision-making methods proposed in the literature of recent years. In this paper, we summarize, review, and categorize research studies that have applied mathematical optimization approaches towards making operational and planning decisions for energy hubs. Relevant methods include robust optimization, information gap decision theory, stochastic programming, and chance-constrained optimization. The results of the review indicate the increasing adoption of robust and, more recently, hybrid methods to deal with the multi-dimensional uncertainties of energy hubs.

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Section: ) Adaptive Robust Optimizationmentioning

confidence: 99%

Section: ) Adaptive Robust Optimizationmentioning

confidence: 99%

Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

et al. 2023

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“…In [26], virtual IESS is regarded as a virtual energy hub (EH), which is defined as a self‐scheduling model of multi‐energy systems participating in various energy markets based on the concept of VPPs. In [27], the VPP function is extended to a multi‐energy system, and the concept of virtual energy stations is proposed. Each distributed energy source participates in the energy market through the integrated energy virtual subject.…”

Section: The Architecture Of Iessmentioning

confidence: 99%

Architecture and function analysis of integrated energy service stations considering cyber‐physical integration

Liu

Wang

Tang

2021

Energy Conversion and Econom

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With the continuing development of the energy internet (EI), the high complexity of multienergy coupling and the dramatic increase in cyber-physical integration impose stricter requirements on the planning and construction of multi-energy systems. The construction of a new energy hub through the intensive use of existing power substation resources is one of the feasible approaches for satisfying these requirements. Integrated energy service stations (IESSs), which comprise substations, multi-energy conversion stations, data centres, communication base stations, and other functional units, constitute the emerging generation of energy and information control centres. IESSs are capable of all-in-one monitoring and energy optimization, and can effectively manage regional energy services involving various energy requirements. This study initially proposes two feasible schemes to realize IESSs: entity IESSs, which require replanning and construction, and virtual IESSs, which involve transformation through existing substation resources. Thereafter, based on the requirements of three types of users, that is high-energy-consumption users, highreliability users, and high-comfort users, the necessity of IESSs in the construction of the EI is analysed in depth. Furthermore, the feasibility of constructing an IESS based on existing power grid resources and the direction for the future development are discussed.

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“…Wu et al, 2018). As far as technical, economic and social standards are concerned, the stochastic strategy surpasses the deterministic method, and it has high potential for real-time power management strategies (S. Yin et al, 2021). In (P. Li et al, 2020), the Lyapunov drift-plus-penalty function is applied to formulate a relaxed form of the energy management problem, more effectively taking into account the uncertainty of energy storage and power load.…”

Section: Introductionmentioning

confidence: 99%

Integrated photovoltaic storage joint smoothing strategy based on simultaneous perturbation stochastic approximation algorithm

Chen²,

Tian³

et al. 2023

Front. Energy Res.

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In order to realize the real-time control of photovoltaic power generation smoothly connected to the grid under the condition that the energy storage equipment can operate safely, a control strategy combining the simultaneous perturbation stochastic approximation (SPSA) algorithm with rule control is designed. Firstly, the photovoltaic data are processed to extract the data characteristics of the power ramp, and then the grid-connected reference power is obtained through SPSA algorithm. Secondly, considering the state of charge (SOC) of energy storage equipment and the safe operating power range of hydrogen storage equipment, 24 hybrid energy storage power allocation rules are formulated by using the rule control method. Finally, according to the sampling data of every 10 s interval in typical day, the simulation is carried out on MATLAB/simulink platform. The results show that, compared with the first-order low-pass filtering algorithm and recursive fuzzy neural network (RFNN) algorithm, the SPSA algorithm has stronger smoothing ability, and the rule control can also complete the allocation according to the characteristics of the hybrid storage device while ensuring its normal operation.

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Energy Pricing and Sharing Strategy Based on Hybrid Stochastic Robust Game Approach for a Virtual Energy Station With Energy Cells

Cited by 31 publications

References 34 publications

Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

Architecture and function analysis of integrated energy service stations considering cyber‐physical integration

Integrated photovoltaic storage joint smoothing strategy based on simultaneous perturbation stochastic approximation algorithm

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