A Probabilistic Model for Minimization of Solar Energy Operation Costs as Well as CO2 Emissions in a Multi-Carrier Microgrid (MCMG)

Ranjbarzadeh, Hassan; Moghaddas-Tafreshi, Seyed Masoud; Ali, Mohd. Hasan; Kouzani, Abbas Z.; Khoo, Suiyang

doi:10.3390/en15093088

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…Moreover, IDRP has on none of the other references have used this too considering hydrogen as the primary energy i ences have considered P2H facilities in their r drogen as the base energy. Additionally, the p [23] es 2023, 16, 631 3 of 24 in the possible scenarios determined by the system operator. A novel stochastic model for hydrogen-and water-based energy hub has been given by Kafaei et al [2] with the aim of minimizing the operation cost and carbon emission.…”

Section: Ref CM Em Moo Dm Edrp Tdrp Eess Hmentioning

confidence: 99%

Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach

et al. 2023

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Nowadays, the integration of multi-energy carriers is one of the most critical matters in smart energy systems with the aim of meeting sustainable energy development indicators. Hydrogen is referred to as one of the main energy carriers in the future energy industry, but its integration into the energy system faces different open challenges which have not yet been comprehensively studied. In this paper, a novel day-ahead scheduling is presented to reach the optimal operation of a hydrogen-based energy hub, based on a stochastic multi-attribute decision-making approach. In this way, the energy hub model is first developed by providing a detailed model of Power-to-Hydrogen (P2H) facilities. Then, a new multi-objective problem is given by considering the prosumer’s role in the proposed energy hub model as well as the integrated demand response program (IDRP). The proposed model introduces a comprehensive approach from the analysis of the historical data to the final decision-making with the aim of minimizing the system operation cost and carbon emission. Moreover, to deal with system uncertainty, the scenario-based method is applied to model the renewable energy resources fluctuation. The proposed problem is defined as mixed-integer non-linear programming (MINLP), and to solve this problem, a simple augmented e-constrained (SAUGMECON) method is employed. Finally, the simulation of the proposed model is performed on a case study and the obtained results show the effectiveness and benefits of the proposed scheme.

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Section: Ref CM Em Moo Dm Edrp Tdrp Eess Hmentioning

confidence: 99%

Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach

et al. 2023

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Day-Ahead Scheduling of Multi-Energy Microgrids Based on a Stochastic Multi-Objective Optimization Model

et al. 2023

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Dealing with multi-objective problems has several interesting benefits, one of which is that it supplies the decision-maker with complete information regarding the Pareto front, as well as a clear overview of the various trade-offs that are involved in the problem. The selection of such a representative set is, in and of itself, a multi-objective problem that must take into consideration the number of choices to show the uniformity of the representation and/or the coverage of the representation in order to ensure the quality of the solution. In this study, day-ahead scheduling has been transformed into a multi-objective optimization problem due to the inclusion of objectives, such as the operating cost of multi-energy multi-microgrids (MMGs) and the profit of the Distribution Company (DISCO). The purpose of the proposed system is to determine the best day-ahead operation of a combined heat and power (CHP) unit, gas boiler, energy storage, and demand response program, as well as the transaction of electricity and natural gas (NG). Electricity and gas are traded by MGs with DISCO at prices that are dynamic and fixed, respectively. Through scenario generation and probability density functions, the uncertainties of wind speed, solar irradiation, electrical, and heat demands have been considered. By using mixed-integer linear programming (MILP) for scenario reduction, the high number of generated scenarios has been significantly reduced. The ɛ-constraint approach was used and solved as mixed-integer nonlinear programming (MINLP) to obtain a solution that meets the needs of both of these nonlinear objective functions.

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A Probabilistic Model for Minimization of Solar Energy Operation Costs as Well as CO2 Emissions in a Multi-Carrier Microgrid (MCMG)

Cited by 2 publications

References 24 publications

Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach

Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach

Day-Ahead Scheduling of Multi-Energy Microgrids Based on a Stochastic Multi-Objective Optimization Model

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