Huzaira Razzaque¹, Shahzaib Ashraf^1,*, Muhammad Naeem², Yu-Ming Chu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1925-1950, 2024, DOI:10.32604/cmes.2023.030030

Abstract Spherical q-linear Diophantine fuzzy sets (Sq-LDFSs) proved more effective for handling uncertainty and vagueness in multi-criteria decision-making (MADM). It does not only cover the data in two variable parameters but is also beneficial for three parametric data. By Pythagorean fuzzy sets, the difference is calculated only between two parameters (membership and non-membership). According to human thoughts, fuzzy data can be found in three parameters (membership uncertainty, and non-membership). So, to make a compromise decision, comparing Sq-LDFSs is essential. Existing measures of different fuzzy sets do, however, can have several flaws that can lead to counterintuitive results. For instance, they treat… More >

Uwem O. Ikitde¹, Abayomi A. Adebiyi^1,*, Innocent E. Davidson², Ayodeji S. Akinyemi¹

Energy Engineering, Vol.120, No.9, pp. 1939-1961, 2023, DOI:10.32604/ee.2023.027574

Abstract The integration of solar and wind energy into the electrical grid has received global research attention due to their unpredictable characteristics. Because wind energy varies across all timescales of utility activity, renewable energy generation should be supplemented and enhanced, from real-time, minute-to-minute variations to annual alterations influencing long-term strategy. Wind energy generation does not only fluctuate but is also challenging to accurately forecast the timeframes of significance to electricity decision makers; day-ahead and long-term making plans of framework sufficiency such as meeting the network peak load annually. A utility that integrates wind and solar energy into its electricity mix would… More >

Muhammad Munsif^1,2, Fath U Min Ullah^1,2, Samee Ullah Khan^1,2, Noman Khan^1,2, Sung Wook Baik^1,2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1751-1773, 2023, DOI:10.32604/csse.2023.038514

Abstract Photovoltaic (PV) systems are environmentally friendly, generate green energy, and receive support from policies and organizations. However, weather fluctuations make large-scale PV power integration and management challenging despite the economic benefits. Existing PV forecasting techniques (sequential and convolutional neural networks (CNN)) are sensitive to environmental conditions, reducing energy distribution system performance. To handle these issues, this article proposes an efficient, weather-resilient convolutional-transformer-based network (CT-NET) for accurate and efficient PV power forecasting. The network consists of three main modules. First, the acquired PV generation data are forwarded to the pre-processing module for data refinement. Next, to carry out data encoding, a… More >

Fatiha Daoudi^1,*, Abdelkrim Naas¹, Omar Meglali^1,2, Radia Boudaira³, Ahmed Gueddim¹, A. M. Saeed⁴

Energy Engineering, Vol.120, No.8, pp. 1803-1815, 2023, DOI:10.32604/ee.2023.028423

Abstract The numerical simulations were performed using the AMPS-1D simulator to study the effects of the CZTS as an absorber layer and the contacts’ barrier height on the performance of four ZnO/CdS/CZTS solar cells. To obtain the best cell performances, the barrier heights of the back and front contacts were adjusted between 0.01, 0.77, 0.5, and 1.55 eV, respectively. For simulations, we used the lifetime mode, and the device performances were evaluated under AM1.5 illumination spectra. We found that the efficiency, fill factor, and open-circuit voltage were almost constant at a front contact barrier height of less than 0.31 eV. The… More > Graphic Abstract

Ming Li^1,*, Cairen Furifu¹, Chengyang Ge², Yunping Zheng¹, Shunfu Lin², Ronghui Liu²

Energy Engineering, Vol.120, No.8, pp. 1775-1801, 2023, DOI:10.32604/ee.2023.027215

Abstract As an effective carrier of integrated clean energy, the microgrid has attracted wide attention. The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the economics and reliability of microgrids. This paper proposes an optimization scheme based on the distributionally robust optimization (DRO) model for a microgrid considering solar-wind correlation. Firstly, scenarios of wind and solar power output scenarios are generated based on non-parametric kernel density estimation and the Frank-Copula function; then the generated scenario results are reduced by K-means clustering; finally, the probability confidence interval of scenario distribution is constrained… More >

Zhenfang Liu^*, Haibo Liu, Dongmei Zhang

Energy Engineering, Vol.120, No.7, pp. 1717-1727, 2023, DOI:10.32604/ee.2023.027968

Abstract To improve the operation efficiency of the photovoltaic power station complementary power generation system, an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed. Particle Swarm Optimization and BP neural network are used to establish the forecasting model, the Markov chain model is used to correct the forecasting error of the model, and the weighted fitting method is used to forecast the annual load curve, to complete the optimal allocation of complementary generating capacity of photovoltaic power stations. The experimental results show that this method reduces the average loss of photovoltaic output… More >

Wenchao Ma^*

Energy Engineering, Vol.120, No.7, pp. 1685-1699, 2023, DOI:10.32604/ee.2023.025404

Abstract The power output state of photovoltaic power generation is affected by the earth's rotation and solar radiation intensity. On the one hand, its output sequence has daily periodicity; on the other hand, it has discrete randomness. With the development of new energy economy, the proportion of photovoltaic energy increased accordingly. In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation, this paper proposes the short-term prediction of photovoltaic power generation based on the improved multi-scale permutation entropy, local mean decomposition and singular spectrum analysis algorithm.… More >

Shekaina Justin^1,*, Wafaa Saleh^1,2, Tasneem Al Ghamdi¹, J. Shermina³

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1091-1109, 2023, DOI:10.32604/iasc.2023.032589

Abstract Renewable energy has become a solution to the world’s energy concerns in recent years. Photovoltaic (PV) technology is the fastest technique to convert solar radiation into electricity. Solar-powered buses, metros, and cars use PV technology. Such technologies are always evolving. Included in the parameters that need to be analysed and examined include PV capabilities, vehicle power requirements, utility patterns, acceleration and deceleration rates, and storage module type and capacity, among others. PVPG is intermittent and weather-dependent. Accurate forecasting and modelling of PV system output power are key to managing storage, delivery, and smart grids. With unparalleled data granularity, a data-driven… More >

Ghaith Yahya Abusaibaa^a , Kamaruzzaman Sopian^a,*, Hasila Jarimi^a , Adnan Ibrahim^a, Saffa Riffat^b

Frontiers in Heat and Mass Transfer, Vol.20, pp. 1-6, 2023, DOI:10.5098/hmt.20.21

Abstract This study will demonstrate the performance of a photovoltaic (PV) powered vapour compression cooling system connected to a Phase Change Material (PCM) storage tank. Three options were studied, namely (a) PV vapour compression with a PCM storage tank and an air-conditioned room with chilled water circulation with transparent membrane/desiccant; (b) PV vapour compression with a PCM storage tank and an air-conditioned room with chilled air dehumidification; and (c) PV vapour compression with a PCM storage tank and an air-conditioned room chilled by combined water circulation, a transparent membrane/desiccant, and air duct dehumidification. Simulation using TRNSYS, TRNBuild, and EES programmes has… More >

Siwei Han^1,*, Xianglong Li², Wei Zhao¹, Linyu Wang¹, Anqi Liang², Shuang Zeng²

Energy Engineering, Vol.120, No.6, pp. 1421-1444, 2023, DOI:10.32604/ee.2023.027094

Abstract Photovoltaics, energy storage, direct current and flexibility (PEDF) are important pillars of achievement on the path to manufacturing nearly zero energy buildings (NZEBs). HVAC systems, which are an important part of public buildings, play a key role in adapting to PDEF systems. This research studied the basic principles and operational control strategies of a DC inverter heat pump using a DC distribution network with the aim of contributing to the development and application of small DC distribution systems. Along with the characteristics of a DC distribution network and different operating conditions, a DC inverter heat pump has the ability to… More >