Techno‐economic optimization of a grid‐connected hybrid energy system considering electric and thermal load prediction

Qiu, Ting; Faraji, Jamal

doi:10.1002/ese3.906

Cited by 24 publications

(20 citation statements)

References 45 publications

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“…(a) In order to have accurate techno-economic values for the grid-connected MG, it is necessary to consider realistic technical and economic data. In this paper, essential economic parameters, such as inflation and discount rates, are assumed as 16.18% and 18%, respectively [69,[93][94][95][96][97]. Furthermore, the simulation lifetime is considered to be 25 years.…”

Section: Case Study and Resultsmentioning

confidence: 99%

Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

et al. 2021

Energies

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The optimal planning of grid-connected microgrids (MGs) has been extensively studied in recent years. While most of the previous studies have used fixed or time-of-use (TOU) prices for the optimal sizing of MGs, this work introduces real-time pricing (RTP) for implementing a demand response (DR) program according to the national grid prices of Iran. In addition to the long-term planning of MG, the day-ahead operation of MG is also analyzed to get a better understanding of the DR program for daily electricity dispatch. For this purpose, four different days corresponding to the four seasons are selected for further analysis. In addition, various impacts of the proposed DR program on the MG planning results, including sizing and best configuration, net present cost (NPC) and cost of energy (COE), and emission generation by the utility grid, are investigated. The optimization results show that the implementation of the DR program has a positive impact on the technical, economic, and environmental aspects of MG. The NPC and COE are reduced by about USD 3700 and USD 0.0025/kWh, respectively. The component size is also reduced, resulting in a reduction in the initial cost. Carbon emissions are also reduced by 185 kg/year.

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Section: Case Study and Resultsmentioning

confidence: 99%

Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

et al. 2021

Energies

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“…Node and pipe temperatures are related, as indicated in (35). The mass flow limitations in (36) are implemented based on the physical characteristics of pipe b of supply and return networks.…”

Section: Endmentioning

confidence: 99%

“…It is possible to use classical and intelligent techniques for predicting uncertain parameters. 32,33 Some of the popular classical methods are autoregressive integrated moving average (ARIMA), 34 exponential smoothing, 35 dynamic regression (DR), 36 and generalized autoregressive conditional heteroskedasticity (GARCH). 37 The most well-known intelligent methods in recent studies are artificial neural networks (ANNs), 38 fuzzy systems, 39 and support vector regression (SVR).…”

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confidence: 99%

Optimization of microenergy grid including adiabatic compressed air energy storage by considering uncertainty of intermittent parameters

Zhan

Arandian

2021

Energy Science & Engineering

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In recent years, zero-carbon energy resources such as adiabatic compressed air energy storage with thermal energy storage have been interested due to growing concerns over global warming. This study proposes a microenergy grid including heat and power networks connected through adiabatic compressed air energy storage with thermal energy storage, which can be considered hybrid energy storage supplying power for both networks. The power network is supplied with How to cite this article: Hu F, Zhan X, Arandian B. Optimization of microenergy grid including adiabatic compressed air energy storage by considering uncertainty of intermittent parameters.

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“…These new energy sources are environmentally friendly, nonpolluting, and cost‐effective, with great reliability. As a result, these energy sources have been hybridized and optimally constructed to meet the desired load using HOMER software 2 . Photovoltaic (PV) is one of the solar green energies that can produce electricity from sunlight via different types of solar cells 3 .…”

Section: Introductionmentioning

confidence: 99%

“…As a result, these energy sources have been hybridized and optimally constructed to meet the desired load using HOMER software. 2 Photovoltaic (PV) is one of the solar green energies that can produce electricity from sunlight via different types of solar cells. 3 In comparison to wind energy, there has been a significant expansion in solar PV capacity, due to its simplicity, throughout the world.…”

Section: Introductionmentioning

confidence: 99%

Enhanced social network search algorithm with powerful exploitation strategy for PV parameters estimation

Shaheen

Elsayed

Ginidi

et al. 2022

Energy Science & Engineering

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In this paper, an enhanced social network search algorithm (ESNSA) has been proposed to model the solar photovoltaic (PV) modules accurately and efficiently. The proposed algorithm is introduced to minimize the least root-mean-square error (RMSE) between the calculated and experimental data for the single, double, and triple diode models of Kyocera KC200GT, STM6(40/36), and Photowatt-PWP201 modules. The original SNSA was inspired by users on social networks and their many moods, including imitation, conversation, disputation, and innovation mood. Two strategies are presented for the ESNSA. The first strategy is the powerful exploitation strategy (PES), which is intended to increase the SNSA's performance by boosting searching around the best view of all users. The second strategy is to suggest an adaptable parameter to aid in the exploitation of iterations in the end. Diverse comparisons and statistical analyses for validation purposes are carried out for mono-crystalline STM6(40/36), multicrystalline KC200GT, and polycrystalline photowatt-PWP201 modules. The comparative studies and statistical measures show the consistency and accurateness of the proposed ESNSA. As a numerical application, for the mono-crystalline STM6(40/36) PV module, the proposed ESNSA achieves the least RMSE of 1.751631E−3, 1.769953E−3, and 1.696504E−3, respectively for the three models. Also, it shows high robustness compared to the original SNSA as it acquires the least standard errors for the three models of 2.56E−18, 1.76E−6, and 1.24E−5, respectively. Moreover, the proposed ESNSA provides a higher convergence speed where it is approximately reached to the least RMSE in less than 60%, 50%, and 60% of the iterations for the three models, respectively. Nevertheless, the proposed ESNSA provides better performance than miscellaneous published approaches in minimizing the RMSE, with high robust indices.

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Techno‐economic optimization of a grid‐connected hybrid energy system considering electric and thermal load prediction

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 24 publications

References 45 publications

Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

Optimization of microenergy grid including adiabatic compressed air energy storage by considering uncertainty of intermittent parameters

Enhanced social network search algorithm with powerful exploitation strategy for PV parameters estimation

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