Multi-objective optimization of a building integrated energy system and assessing the effectiveness of supportive energy policies in Iran

Naserabad, Sadegh Nikbakht; Rafee, Roohollah; Saedodin, Seyfolah; Ahmadi, Pouria

doi:10.1016/j.seta.2021.101343

Cited by 10 publications

(1 citation statement)

References 42 publications

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“…The VIKOR method is used to make optimal decisions on the solution set. Finally, a BIES in the north is used as a case study to verify that the proposed method can effectively balance the economy, environmental protection, and comfort of system operation [10] [11].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Building Integrated Energy System Considering Demand Response and User Comfort

Zhou,

Qin,

Wang

et al. 2024

Frontiers in Artificial Intelligence and Applications

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The building itself has a certain thermal inertia, which makes the energy supply process of the energy system flexible. At the same time, the comfort of the user should be ensured in the process of building energy supply adjustment. To solve the above problems, this paper proposes a considering demand response (DR) and user comfort of building integrated energy system (BIES) multi-objective optimization method. Firstly, a typical BIES model and a device power model are constructed. Secondly, according to the price elasticity matrix and building thermal inertia, the price-type and regulation-type DR models are constructed. Then, according to the economic, environmental protection, and comfort requirements of the BIES, considering the constraints of power balance, equipment operation, DR, and so on, the BIES optimal scheduling model is established. The multi-objective gray wolf optimizer (MOGWO) algorithm is optimized by chaos operator and t distribution. The model is solved and the optimized algorithm is to obtain the Pareto optimal solution set, using the VIKOR method for the optimal decision solution set. Finally, the BIES in a building is used as an example for analysis, and the results show that the proposed method can effectively balance the efficiency of system operation, environmental protection, and energy efficiency.

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Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Building Integrated Energy System Considering Demand Response and User Comfort

Zhou,

Qin,

Wang

et al. 2024

Frontiers in Artificial Intelligence and Applications

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Artificial intelligence‐based tri‐objective optimization of different demand load patterns on the optimal sizing of a smart educational buildings

Hosseini

Naserabad

Keshavarzzadeh

et al. 2022

Intl J of Energy Research

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In this research, an integrated energy system for providing triple loads of an educational building has been modeled, analyzed, and optimized using artificial intelligence The use of different load supply patterns for the integrated system was optimized and evaluated from the point of view of exergy, economics, and environment. SketchUp, OpenStudio, and EnergyPlus are used to obtain the building loads, and the integrated system is dynamically modeled by the MATLAB software. The integrated system has been optimized based on different patterns, including monthly, seasonal, and two-state constant loads compared with hourly dynamic loads using an artificial intelligence genetic algorithm. The results show that the dynamic load pattern gives the highest exergy efficiency and the lowest total cost rate. The exergy efficiency and total cost rate in this scenario are 58.78% and 5.022 $/h, respectively. Also, the CO 2 emission index has reached 363.1 g/kWh. Due to the subsidized price of grid electricity, there is a tendency to use low-capacity gas turbines and buy electricity from the grid for the dynamic model. The gas turbine capacity is 35.56 kW, and the system has purchased 242.4 MWh from the grid. Due to high heating loads, the capacity of the gas turbine significantly increases, and no electricity is purchased from the grid in the fixed-load pattern. The highest capacity of the gas turbine is 161.6 kW, which is obtained by a seasonal fixedload pattern. Also, 994.9 MWh of electricity is sold to the grid in this mode.

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The development of a new thermal modeling and heat transfer mechanisms of a compound parabolic concentrator (CPC) based on nanofluids

Khaledi

Saedodin

Rostamian

2023

J Therm Anal Calorim

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Multi-objective optimization of a building integrated energy system and assessing the effectiveness of supportive energy policies in Iran

Cited by 10 publications

References 42 publications

Multi-Objective Optimization of Building Integrated Energy System Considering Demand Response and User Comfort

Multi-Objective Optimization of Building Integrated Energy System Considering Demand Response and User Comfort

Artificial intelligence‐based tri‐objective optimization of different demand load patterns on the optimal sizing of a smart educational buildings

The development of a new thermal modeling and heat transfer mechanisms of a compound parabolic concentrator (CPC) based on nanofluids

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