Saqib Ali^1,2, Shazia Riaz^2,3, Safoora², Xiangyong Liu¹, Guojun Wang^1,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1783-1800, 2023, DOI:10.32604/cmc.2023.035736 - 06 February 2023

Abstract Short-term load forecasting (STLF) is part and parcel of the efficient working of power grid stations. Accurate forecasts help to detect the fault and enhance grid reliability for organizing sufficient energy transactions. STLF ranges from an hour ahead prediction to a day ahead prediction. Various electric load forecasting methods have been used in literature for electricity generation planning to meet future load demand. A perfect balance regarding generation and utilization is still lacking to avoid extra generation and misusage of electric load. Therefore, this paper utilizes Levenberg–Marquardt (LM) based Artificial Neural Network (ANN) technique to… More >

Haibo Li^1,*, Yibao Wang¹, Xinfu Pang¹, Wei Liu¹, Xu Zhang²

Energy Engineering, Vol.120, No.2, pp. 317-343, 2023, DOI:10.32604/ee.2023.023715 - 29 November 2022

Abstract Electric-heat coupling characteristics of a cogeneration system and the operating mode of fixing electricity with heat are the main reasons for wind abandonment during the heating season in the Three North area. To improve the wind-power absorption capacity and operating economy of the system, the structure of the system is improved by adding a heat storage device and an electric boiler. First, aiming at the minimum operating cost of the system, the optimal scheduling model of the cogeneration system, including a heat storage device and electric boiler, is constructed. Second, according to the characteristics of… More >

Xing Deng^1,2, Feipeng Da^1,*, Haijian Shao², Xia Wang³

Energy Engineering, Vol.120, No.2, pp. 385-408, 2023, DOI:10.32604/ee.2023.023480 - 29 November 2022

Abstract Photovoltaic power generating is one of the primary methods of utilizing solar energy resources, with large-scale photovoltaic grid-connected power generation being the most efficient way to fully utilize solar energy. In order to provide reference strategies for pertinent researchers as well as potential implementation, this paper tries to provide a survey investigation and technical analysis of machine learning-related approaches, statistical approaches and optimization techniques for solar power generation and forecasting. Deep learning-related methods, in particular, can theoretically handle arbitrary nonlinear transformations through proper model structural design, such as hidden layer topology optimization and objective function More > Graphic Abstract

Yu Xiao^1,2, Kai Li^1,2, Hongqiao Huang^1,2, Haibo Tan^1,2, Hua Li^3,*

Energy Engineering, Vol.120, No.2, pp. 511-527, 2023, DOI:10.32604/ee.2023.022750 - 29 November 2022

Abstract The analysis of the loss of distributed photovoltaic power generation systems involves the interests of energy users, energy-saving service companies, and power grid companies, so it has always been the focus of the industry and society in some manner or another. However, the related analysis for an actual case that considers different cooperative corporations’ benefits is lacking in the presently available literature. This paper takes the distributed rooftop photovoltaic power generation project in an industrial park as the object, studies the analysis and calculation methods of line loss and transformer loss, analyzes the change of… More >

Tao Hou¹, Shan Wang^1,2,*

Energy Engineering, Vol.120, No.1, pp. 87-106, 2023, DOI:10.32604/ee.2022.022122 - 27 October 2022

Abstract The existing Maximum Power Point Tracking (MPPT) method has low tracking efficiency and poor stability. It is easy to fall into the Local Maximum Power Point (LMPP) in Partial Shading Condition (PSC), resulting in the degradation of output power quality and efficiency. It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms, and their performance in tracking the Global Maximum Power Point (GMPP) varies. Thus, a Cuckoo search algorithm (CSA) combined with the Incremental conductance Algorithm (INC) is proposed (CSA-INC) is put forward for the MPPT method of photovoltaic power generation. The More > Graphic Abstract

Ulagammai Meyyappan^*, S. Joyal Isac

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 399-413, 2023, DOI:10.32604/iasc.2023.026627 - 06 June 2022

Abstract Demand Response (DR) is one of the most cost-effective and unfailing techniques used by utilities for consumer load shifting. This research paper presents different DR programs in deregulated environments. The description and the classification of DR along with their potential benefits and associated cost components are presented. In addition, most DR measurement indices and their evaluation are also highlighted. Initially, the economic load model incorporated thermal, wind, and energy storage by considering the elasticity market price from its calculated locational marginal pricing (LMP). The various DR programs like direct load control, critical peak pricing, real-time More >

Thakrittorn Pansiri¹, Attakorn Asanakham^2,*, Thoranis Deethayat², Tanongkiat Kiatsiriroat²

Energy Engineering, Vol.119, No.5, pp. 1861-1878, 2022, DOI:10.32604/ee.2022.022332 - 21 July 2022

Abstract This paper proposed a new function of photovoltaic thermal (PVT) module to produce nocturnal cool water not just only generating electrical power and hot water during daytime. Experimental tests were carried out under Chiang Mai tropical climate with a 200 Wp monocrystalline PVT module having dimensions of 1.601 m × 0.828 m connected with two water tanks each of 60 L taken for hot and cool water storages. The module was facing south with 18^o inclination. The electrical load was a 200 W halogen lamp. From experiments, by taking the module as a nocturnal radiative cooling surface, the… More > Graphic Abstract

Zhongyao Du^1,*, Xiaoying Chen¹, Hao Wang², Xuheng Wang¹, Yu Deng¹, Liying Sun¹

Energy Engineering, Vol.119, No.4, pp. 1419-1438, 2022, DOI:10.32604/ee.2022.020283 - 23 May 2022

Abstract To attain the goal of carbon peaking and carbon neutralization, the inevitable choice is the open sharing of power data and connection to the grid of high-permeability renewable energy. However, this approach is hindered by the lack of training data for predicting new grid-connected PV power stations. To overcome this problem, this work uses open and shared power data as input for a short-term PV-power-prediction model based on feature transfer learning to facilitate the generalization of the PV-power-prediction model to multiple PV-power stations. The proposed model integrates a structure model, heat-dissipation conditions, and the loss… More >

K. R. Chairma Lakshmi^*, Geetha Ramadas

Journal of Renewable Materials, Vol.10, No.8, pp. 2133-2153, 2022, DOI:10.32604/jrm.2022.019649 - 25 April 2022

Abstract A solar PV panel works with maximum efficiency only when it is operated around its optimum operating point or maximum power point. Unfortunately, the performance of the solar cell is affected by several factors like sun direction, solar irradiance, dust accumulation, module temperature, as well as the load on the system. Dust deposition is one of the most prominent factors that influence the performance of solar panels. Because the solar panel is exposed to the atmosphere, dust will accumulate on its surface, reducing the quantity of sunlight reaching the solar cell and diminishing output. In… More >

Pudi Sekhar¹, T. J. Benedict Jose², Velmurugan Subbiah Parvathy³, E. Laxmi Lydia⁴, Seifedine Kadry⁵, Kuntha Pin⁶, Yunyoung Nam^7,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1473-1487, 2022, DOI:10.32604/cmc.2022.022110 - 03 November 2021

Abstract With the incorporation of distributed energy systems in the electric grid, transactive energy market (TEM) has become popular in balancing the demand as well as supply adaptively over the grid. The classical grid can be updated to the smart grid by the integration of Information and Communication Technology (ICT) over the grids. The TEM allows the Peer-to-Peer (P2P) energy trading in the grid that effectually connects the consumer and prosumer to trade energy among them. At the same time, there is a need to predict the load for effectual P2P energy trading and can be… More >