A robust optimization framework for energy management of CCHP users with integrated demand response in electricity market

Chen, Lingmin; Tang, Huiling; Jiekang, Wu; Changjie, Li; Wang, Yanan

doi:10.1016/j.ijepes.2022.108181

Cited by 46 publications

(10 citation statements)

References 38 publications

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“…The time-sharing purchase electricity price and gas price are shown in Fig 4D [ 40 ]. Micro-source equipment correlation coefficient are shown in S3 Table [ 24 , 41 ]. Prices for the maintenance of related equipment are shown in S4 Table [ 24 , 41 ].…”

Section: Analysis Of Examplesmentioning

confidence: 99%

“…Micro-source equipment correlation coefficient are shown in S3 Table [ 24 , 41 ]. Prices for the maintenance of related equipment are shown in S4 Table [ 24 , 41 ]. Carbon tax price is set to 20 $/t [ 42 ].…”

Section: Analysis Of Examplesmentioning

confidence: 99%

“…In this study, the parameters of the pumped storage power station in [36], hourly electrical, heating, and cooling loads data in [37], the fluctuation in the demand for desalinated water in a 24-hour period [18], and the time-varying curve of wind energy, solar energy in [38] are referred for model construction and algorithm solution. Among them, pumped storage unit related data are presented in S1 Refer to micro-source equipment parameters and energy prices in [24,36,[39][40][41][42][43][44] to make the following settings. The maximum output power and minimum output power of the gas turbine are 114 MW and 28.5 MW, respectively.…”

Section: Basic Datamentioning

confidence: 99%

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Integrated energy system optimal scheduling considering the comprehensive and flexible operation mode of pumping storage

et al. 2022

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The integrated energy system (IES) optimal scheduling under the comprehensive flexible operation mode of pumping storage is considered. This system is conducive to the promotion of the accommodation of wind and solar energy and can meet the water, electricity and heat needs of coastal areas far away from the energy center. In this study, the joint dispatch between double pumped storage power stations is used to accommodate wind and solar energy better and smooth their fluctuations on the grid. Through the scheduling of water between the high and low reservoirs of double pumped storage power stations and the reservoir of the seawater desalination plant, the impact of storage capacity constraints on pumped storage power plants is reduced. Moreover, the objective function to build the IES optimization scheduling model is to achieve minimum economic cost. The results reveal that the integrated energy system accommodates all wind energy and solar energy. As such, the system increases the average working time of the pumped storage unit by 1.9 hours and reduces the economic cost by 31.50%. Based on the simulation results, the model can enhance the accommodation capability of wind energy and solar energy and improve the system economy.

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Section: Analysis Of Examplesmentioning

confidence: 99%

Section: Analysis Of Examplesmentioning

confidence: 99%

Section: Basic Datamentioning

confidence: 99%

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Integrated energy system optimal scheduling considering the comprehensive and flexible operation mode of pumping storage

et al. 2022

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“…Therefore, RO is introduced as a better way to alleviate the above shortcomings. Based on the analysis of power systems under various uncertainties, the UC schedule generated by RO performs well in the worst case (Chen et al, 2022 ). In the literature (Gupta & Anderson, 2019 ), robust unit commitment (RUC) method based on the feature sorting algorithm used in the traditional pattern recognition problem was proposed, which is flexible on the basis of considering all cases.…”

Section: Introductionmentioning

confidence: 99%

Scenario-Based Distributionally Robust Unit Commitment Optimization Involving Cooperative Interaction with Robots

et al. 2022

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With the increasing penetration of renewable energy, uncertainty has become the main challenge of power systems operation. Fortunately, system operators could deal with the uncertainty by adopting stochastic optimization (SO), robust optimization (RO) and distributionally robust optimization (DRO). However, choosing a good decision takes much experience, which can be difficult when system operators are inexperienced or there are staff shortages. In this paper, a decision-making approach containing robotic assistance is proposed. First, advanced clustering and reduction methods are used to obtain the scenarios of renewable generation, thus constructing a scenario-based ambiguity set of distributionally robust unit commitment (DR-UC). Second, a DR-UC model is built according to the above time-series ambiguity set, which is solved by a hybrid algorithm containing improved particle swarm optimization (IPSO) and mathematical solver. Third, the above model and solution algorithm are imported into robots that assist in decision making. Finally, the validity of this research is demonstrated by a series of experiments on two IEEE test systems.

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“…Robust optimization is a functional technique to handle uncertainties, and is mostly free from the flaws mentioned above (Jabbarzadeh, Haughton, & Pourmehdi, 2019). Both fuzzy optimization and stochastic optimization rely on probability distribution of random variables (L. Chen, Tang, Wu, Li, & Wang, 2022), which, once correctly identified, can accurately reflect the uncertain characteristics of random variables. However, obtaining the precise probability distribution information is closely related to the number of data samples as well as the accuracy of the prediction methods.…”

Section: Introductionmentioning

confidence: 99%

A robust optimization model for green supplier selection and order allocation in a closed-loop supply chain considering cap-and-trade mechanism

Mirzaee¹,

Samarghandi²,

Willoughby³

2022

Preprint

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Due to increasing air pollution, which is a consequence of the environmental effects of production in various industries, green supply chain management (GSCM) has attracted the attention of both scholars and practitioners. Green supplier selection is one of the most important problems in GSCM, which satisfies a firm's environmental goals as well as its economic targets. In this paper, for the first time, a green supplier

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A robust optimization framework for energy management of CCHP users with integrated demand response in electricity market

Cited by 46 publications

References 38 publications

Integrated energy system optimal scheduling considering the comprehensive and flexible operation mode of pumping storage

Integrated energy system optimal scheduling considering the comprehensive and flexible operation mode of pumping storage

Scenario-Based Distributionally Robust Unit Commitment Optimization Involving Cooperative Interaction with Robots

A robust optimization model for green supplier selection and order allocation in a closed-loop supply chain considering cap-and-trade mechanism

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