An Optimal Energy Hub Management Integrated EVs and RES Based on Three-Stage Model Considering Various Uncertainties

Mokaramian, Elham; Shayeghi, Hossein; Sedaghati, Farzad; Safari, Amin; Alhelou, Hassan Haes

doi:10.1109/access.2022.3146447

Cited by 45 publications

(8 citation statements)

References 38 publications

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“…The boiler can produce thermal energy to supply the thermal demand. In this equipment, the thermal energy is limited by (11), such that the conversion of NG into heat is modelled in (12). Moreover, the HRV coefficient is the heat rate value [16].…”

Section: Ng-based Boilermentioning

confidence: 99%

“…In Ref. [11], a two‐objective optimization problem, considering economic and environmental issues, is presented for the day‐ahead operation of an EH with electricity, thermal, and NG demands, and also electric vehicles. Reference [12] dissected the efficiency of an EH by using a multi‐objective function consisting of economic operation, environmental problem, load deviation, and risk.…”

Section: Introductionmentioning

confidence: 99%

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Economic‐environmental operation of a CHHP energy hub considering uncertainties and demand response programs

Ghappani,

Karimi

2023

IET Generation Trans & Dist

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According to the necessity of cost‐effectiveness, improving efficiency, and decreasing emissions to supply the various demands, the concept of energy hubs (EHs) has emerged in recent years. This paper aims to ensure the optimal operation of an EH to meet electrical, thermal, and hydrogen demands, considering the issues of pollutant emission and operating costs. In the proposed structure for the EH, an solid oxid fuel cell (SOFC) converter with ammonia fuel is used, and thus a combined hydrogen, heat, and power (CHHP) system is formed. Moreover, a basic EH structure is also examined and compared to show the capability of the presented structure. The proposed economic‐environmental framework for the operation of the EH is multi‐objective as a stochastic mixed‐integer linear programming (MILP). Also, in addition to modelling the uncertainty of renewable sources production as stochastic scenarios, demand response programs (DRPs) have been implemented for electrical and thermal demands. The ε‐constraint method is used to solve the multi‐objective problem, and the fuzzy technique is applied to select the best solution among the Pareto solutions. The simulation results of the proposed EH compared to the basic EH show that the operation cost and emission are decreased by 15.14% and 5.9%, respectively, in the presence of ammonia and DRP.

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Section: Ng-based Boilermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Economic‐environmental operation of a CHHP energy hub considering uncertainties and demand response programs

Ghappani,

Karimi

2023

IET Generation Trans & Dist

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“…The EH model consumes energy at its entrance, such as power and natural gas infrastructure, and provides necessary energy services at its output side. For the EH model, energy is converted in different forms through coupling devices, including combined heat and power (CHP) units, electric boilers (EB), and absorption chillers [28][29][30][31].…”

Section: System Modelmentioning

confidence: 99%

Two-Stage Scheduling Strategy for Integrated Energy Systems Considering Renewable Energy Consumption

Liu¹,

Xie²,

Tian³

et al. 2022

IEEE Access

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With the crisis of energy and environment, the integrated energy systems (IES) have a bright prospect in future energy reform owing to the excellent economic and environmental performance. The IES combines a large amount of renewable energy (RE), which guarantees its economic and environmental benefits. Many uncertainties of RE threaten the performance of IES. How to promote RE consumption under strong uncertainties is a crucial problem in the scheduling of IES. In this work, a two-stage scheduling strategy for IES combining day-ahead scheduling and real-time scheduling is proposed to guide the system operation. The stage of day-ahead scheduling can obtain the optimal scheduling scheme one day in advance based on the forecast data of RE, and the stage of real-time scheduling is introduced to cope with the uncertainties of RE. The model of IES is established based on the energy hub (EH), and the entire strategy is implemented on this model. The model integrates various energy conversion equipment to give full play to the advantages of coordination and complementation of IES. The improved particle swarm optimization (IPSO) is proposed as the solution algorithm of the whole strategy, which improves the traditional PSO through random nonlinearity change inertia weight strategy and best solution perturbation operator (BSPO). Compared with the traditional PSO, IPSO has more excellent performance for solving IES scheduling model. Finally, different schemes under different situations are compared.

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“…A multiple time scale optimization model is proposed in Zhou et al, 2021 to address the uncertainties of flexible load and renewable energy sources (RESs). In Mokaramian et al, 2022, an energy hub (EH) system containing DGs is proposed to enhance system coupling and optimize demand supply, system reliability, and energy management. Meanwhile, the uncertainty model is constructed based on the stochastic optimization method, improving the system reliability.…”

Section: Introductionmentioning

confidence: 99%

Robust optimization of the active distribution network involving risk assessment

Yang

Zhang

et al. 2022

Front. Energy Res.

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Inherent dynamic constraints of distributed generations (DGs) and the correlation between injected variables bring great challenges to distribution network operation. In order to improve the degree of coupling and interconnection coordination between different energy devices, improve the ability of the distribution network to cope with the uncertainty of DGs, achieve low-carbon operation, and improve the environmental friendliness of distribution network operation, this article proposes a robust optimization approach involving risk assessment. The semi-invariant method and scene clustering are used to deal with the uncertainty of DGs and load, thus formulating a robust optimization model for distribution network distribution based on risk indices. To address the time-varying constraints of energy storage systems (ESSs) and gas turbines, a two-stage box-based decomposition model is established. Dynamic constraints are included in the first stage to constrain the operating state and operating domain of the unit and ESSs. In the second stage, the multi-timescale optimization problem is transformed into multiple single-timescale optimization problems, which are solved by the column and constraint generation (C&CG) algorithm to improve the solution efficiency. The feasibility of the comprehensive optimization model based on dynamic reconfiguration and distributed robust optimization (DRO) is demonstrated with the PG&E 69 bus system.

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An Optimal Energy Hub Management Integrated EVs and RES Based on Three-Stage Model Considering Various Uncertainties

Cited by 45 publications

References 38 publications

Economic‐environmental operation of a CHHP energy hub considering uncertainties and demand response programs

Economic‐environmental operation of a CHHP energy hub considering uncertainties and demand response programs

Two-Stage Scheduling Strategy for Integrated Energy Systems Considering Renewable Energy Consumption

Robust optimization of the active distribution network involving risk assessment

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