Yujin Liu¹, Zhenkai Zhang¹, Li Ma¹, Yan Jia^1,2,*, Weihua Yin³, Zhifeng Liu³

Energy Engineering, Vol.121, No.10, pp. 3019-3035, 2024, DOI:10.32604/ee.2024.052594 - 11 September 2024

Abstract Accurate short-term photovoltaic (PV) power prediction helps to improve the economic efficiency of power stations and is of great significance to the arrangement of grid scheduling plans. In order to improve the accuracy of PV power prediction further, this paper proposes a data cleaning method combining density clustering and support vector machine. It constructs a short-term PV power prediction model based on particle swarm optimization (PSO) optimized Long Short-Term Memory (LSTM) network. Firstly, the input features are determined using Pearson’s correlation coefficient. The feature information is clustered using density-based spatial clustering of applications with noise More >

Cuiping Li¹, Kunqi Gao¹, Can Chen², Junhui Li^1,*, Xiaoxiao Wang², Yinchi Shao², Xingxu Zhu¹

Energy Engineering, Vol.121, No.10, pp. 2937-2959, 2024, DOI:10.32604/ee.2024.052167 - 11 September 2024

Abstract In recent years, distributed photovoltaics (DPV) has ushered in a good development situation due to the advantages of pollution-free power generation, full utilization of the ground or roof of the installation site, and balancing a large number of loads nearby. However, under the background of a large-scale DPV grid-connected to the county distribution network, an effective analysis method is needed to analyze its impact on the voltage of the distribution network in the early development stage of DPV. Therefore, a DPV orderly grid-connected method based on photovoltaics grid-connected order degree (PGOD) is proposed. This method… More >

Weidong Chen^1,2,*, Yun Zhao³, Xiaorui Wu^1,2, Ziwen Cai³, Min Guo^1,2, Yuxin Lu³

Energy Engineering, Vol.121, No.10, pp. 3075-3093, 2024, DOI:10.32604/ee.2024.051404 - 11 September 2024

Abstract The integration of photovoltaic, energy storage, direct current, and flexible load (PEDF) technologies in building power systems is an important means to address the energy crisis and promote the development of green buildings. The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid. For this purpose, this work introduces a framework of multiple incentive mechanisms for a PEDF park, a building energy system that implements PEDF technologies. The incentive mechanisms proposed in this paper include both economic and noneconomic… More >

Amal El Berry, Marwa M. Ibrahim^*, A. A. Elfeky, Mohamed F. Nasr

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1189-1207, 2024, DOI:10.32604/fhmt.2024.050684 - 30 August 2024

Abstract A photovoltaic (PV) inverter is a vital component of a photovoltaic (PV) solar system. Photovoltaic (PV) inverter failure can mean a solar system that is no longer functioning. When electronic devices such as photovoltaic (PV) inverter devices are subjected to vapor condensation, a risk could occur. Given the amount of moisture in the air, saturation occurs when the temperature drops to the dew point, and condensation may form on surfaces. Numerical simulation with “COMSOL Software” is important for obtaining knowledge relevant to preventing condensation by using two steps. At first, the assumption was that the… More >

Rittick Maity^1,2, Muhammad Khairul Imran bin Ahmad Shuhaimi³, Kumarasamy Sudhakar^3,4,5,*, Amir Abdul Razak³

Energy Engineering, Vol.121, No.9, pp. 2331-2361, 2024, DOI:10.32604/ee.2024.051576 - 19 August 2024

Abstract The United Nations’ Sustainable Development Goals (SDGs) highlight the importance of affordable and clean energy sources. Solar energy is a perfect example, being both renewable and abundant. Its popularity shows no signs of slowing down, with solar photovoltaic (PV) panels being the primary technology for converting sunlight into electricity. Advancements are continuously being made to ensure cost-effectiveness, high-performing cells, extended lifespans, and minimal maintenance requirements. This study focuses on identifying suitable locations for implementing solar PV systems at the University Malaysia Pahang Al Sultan Abdullah (UMPSA), Pekan campus including buildings, water bodies, and forest areas.… More > Graphic Abstract

Kaicheng Liu^1,3, Chen Liang², Naiyue Wu^1,3, Xiaoyang Dong², Hui Yu^1,*

Energy Engineering, Vol.121, No.9, pp. 2621-2637, 2024, DOI:10.32604/ee.2024.050001 - 19 August 2024

Abstract This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices. This method integrates features including photovoltaic (PV) systems, energy storage coupling, varied energy roles, and energy supply and demand dynamics. The system model is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously. To strike a balance between optimality and feasibility, renewable energy resources are modeled with considerations for forecasting errors, Gaussian distribution, and penalty factors. Furthermore, this study introduces a distributed event-triggered surplus algorithm designed to address the More >

Jiaxin Qiao¹, Yuchen Hao², Yingqi Liao³, Fang Liang³, Jing Bian^1,*

Energy Engineering, Vol.121, No.9, pp. 2655-2680, 2024, DOI:10.32604/ee.2024.049509 - 19 August 2024

Abstract The massive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations. To accurately assess the flexible regulation capabilities of distribution stations, a multi-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics, considering different geographical locations, coverage areas, and response capabilities. Firstly, the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed, and a resource regulation capability model is established to quantify the adjustable range of different regulation resources. On… More >

Jiarui Zhang¹, Dan Liu^2,*, Kan Cao², Ping Xiong², Xiaotong Ji³, Yanze Xu¹, Yunfei Mu¹

Energy Engineering, Vol.121, No.8, pp. 2065-2083, 2024, DOI:10.32604/ee.2024.050342 - 19 July 2024

Abstract The system performance of grid-connected photovoltaic (PV) has a serious impact on the grid stability. To improve the control performance and shorten the convergence time, a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic. The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect. To address the “computational explosion problem” in the design process of backstepping control, dynamic surface control is adopted to avoid the analytical calculations of virtual control. The disturbances of the PV system are estimated and More >

Yang Li^1,2, Jianjun Zhao², Xiaolong Yang², He Wang^1,*, Yuyan Wang¹

Energy Engineering, Vol.121, No.5, pp. 1263-1289, 2024, DOI:10.32604/ee.2024.046784 - 30 April 2024

Abstract Distributed photovoltaic (PV) is one of the important power sources for building a new power system with new energy as the main body. The rapid development of distributed PV has brought new challenges to the operation of distribution networks. In order to improve the absorption ability of large-scale distributed PV access to the distribution network, the AC/DC hybrid distribution network is constructed based on flexible interconnection technology, and a coordinated scheduling strategy model of hydrogen energy storage (HS) and distributed PV is established. Firstly, the mathematical model of distributed PV and HS system is established,… More >

Lifeng Li¹, Zaimin Yang¹, Xiongping Yang¹, Jiaming Li², Qianyufan Zhou^3,*, Ping Yang³

Energy Engineering, Vol.121, No.5, pp. 1329-1346, 2024, DOI:10.32604/ee.2023.046447 - 30 April 2024

Abstract As the global demand for renewable energy grows, solar energy is gaining attention as a clean, sustainable energy source. Accurate assessment of solar energy resources is crucial for the siting and design of photovoltaic power plants. This study proposes an integrated deep learning-based photovoltaic resource assessment method. Ensemble learning and deep learning methods are fused for photovoltaic resource assessment for the first time. The proposed method combines the random forest, gated recurrent unit, and long short-term memory to effectively improve the accuracy and reliability of photovoltaic resource assessment. The proposed method has strong adaptability and More >