Yongjiang Zhao, Haoyi Zhong, Chang Cyoon Lim^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 449-471, 2024, DOI:10.32604/cmc.2024.048771

Abstract This paper examines the difficulties of managing distributed power systems, notably due to the increasing use of renewable energy sources, and focuses on voltage control challenges exacerbated by their variable nature in modern power grids. To tackle the unique challenges of voltage control in distributed renewable energy networks, researchers are increasingly turning towards multi-agent reinforcement learning (MARL). However, MARL raises safety concerns due to the unpredictability in agent actions during their exploration phase. This unpredictability can lead to unsafe control measures. To mitigate these safety concerns in MARL-based voltage control, our study introduces a novel approach: Safety-Constrained Multi-Agent Reinforcement Learning… More >

Mousumi Basu¹, Chitralekha Jena², Baseem Khan^3,4,*, Ahmed Ali⁴

Energy Engineering, Vol.121, No.4, pp. 849-867, 2024, DOI:10.32604/ee.2024.043294

Abstract In the restructured electricity market, microgrid (MG), with the incorporation of smart grid technologies, distributed energy resources (DERs), a pumped-storage-hydraulic (PSH) unit, and a demand response program (DRP), is a smarter and more reliable electricity provider. DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines. Better bidding strategies, prepared by MG operators, decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources (RES). But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate. To solve these issues, this study… More >

Yan Shi¹, Wenjie Li¹, Gongbo Fan^2,*, Luxi Zhang¹, Fengjiu Yang¹

Energy Engineering, Vol.121, No.2, pp. 461-482, 2024, DOI:10.32604/ee.2023.043835

Abstract Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation, this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side. A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation, with the overarching goal of optimizing the system for low-carbon operation. To begin with, an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side… More >

Qin Yao, Yida Zeng^*, Qingui Jia

Energy Engineering, Vol.121, No.1, pp. 221-241, 2024, DOI:10.32604/ee.2023.041028

Abstract In recent years, switched inductor (SL) technology, switched capacitor (SC) technology, and switched inductor-capacitor (SL-SC) technology have been widely applied to optimize and improve DC-DC boost converters, which can effectively enhance voltage gain and reduce device stress. To address the issue of low output voltage in current renewable energy power generation systems, this study proposes a novel non-isolated cubic high-gain DC-DC converter based on the traditional quadratic DC-DC boost converter by incorporating a SC and a SL-SC unit. Firstly, the proposed converter’s details are elaborated, including its topology structure, operating mode, voltage gain, device stress, and power loss. Subsequently, a… More >

Abdennasser Dahmani¹, Yamina Ammi², Nadjem Bailek^3,4,*, Alban Kuriqi^5,6, Nadhir Al-Ansari^7,*, Salah Hanini², Ilhami Colak⁸, Laith Abualigah^{9,10,11,12,13,14}, El-Sayed M. El-kenawy¹⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2579-2594, 2023, DOI:10.32604/cmc.2023.040625

Abstract Increasing global energy consumption has become an urgent problem as natural energy sources such as oil, gas, and uranium are rapidly running out. Research into renewable energy sources such as solar energy is being pursued to counter this. Solar energy is one of the most promising renewable energy sources, as it has the potential to meet the world’s energy needs indefinitely. This study aims to develop and evaluate artificial intelligence (AI) models for predicting hourly global irradiation. The hyperparameters were optimized using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton training algorithm and STATISTICA software. Data from two stations in Algeria with different climatic… More >

Ju Hyeon Lee¹, Jiho Shin², Jung Taek Seo^3,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 757-779, 2023, DOI:10.32604/cmc.2023.039461

Abstract As energy-related problems continue to emerge, the need for stable energy supplies and issues regarding both environmental and safety require urgent consideration. Renewable energy is becoming increasingly important, with solar power accounting for the most significant proportion of renewables. As the scale and importance of solar energy have increased, cyber threats against solar power plants have also increased. So, we need an anomaly detection system that effectively detects cyber threats to solar power plants. However, as mentioned earlier, the existing solar power plant anomaly detection system monitors only operating information such as power generation, making it difficult to detect cyberattacks.… More >

Weigang Jin¹, Lei Chen^2,*, Yifei Li², Shencong Zheng², Yuqi Jiang², Hongkun Chen²

Energy Engineering, Vol.120, No.11, pp. 2469-2487, 2023, DOI:10.32604/ee.2023.043021

Abstract Along with the increasing integration of renewable energy generation in AC-DC power networks, investigating the dynamic behaviors of this complex system with a proper equivalent model is significant. This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator (DFIG) based wind farms to decrease the simulation scale and computational burden. For the AC-DC power networks, the equivalent modeling strategy in accordance with the physical structure simplification is stated. Regarding the DFIG-based wind farms, the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm (ICCSA) is conducted.… 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 >

Yanjun Yan, Kai Chen^*, Hang Geng, Wenqian Fan, Xinrui Zhou

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1345-1379, 2023, DOI:10.32604/cmes.2023.027252

Abstract With increasing global concerns about clean energy in smart grids, the detection of power quality disturbances (PQDs) caused by energy instability is becoming more and more prominent. It is well acknowledged that the PQD effects on power grid equipment are destructive and hazardous, which causes irreversible damage to underlying electrical/electronic equipment of the concerned intelligent grids. In order to ensure safe and reliable equipment implementation, appropriate PQD detection technologies must be adopted to avoid such adverse effects. This paper summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start to new researchers in the… More > Graphic Abstract

N. Kanagaraj^1,*, Obaid Aldosari¹, M. Ramasamy², M. Vijayakumar²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2291-2306, 2023, DOI:10.32604/iasc.2023.039101

Abstract The generation of electricity, considering environmental and economic factors is one of the most important challenges of recent years. In this article, a thermoelectric generator (TEG) is proposed to use the thermal energy of an electric water heater (EWH) to generate electricity independently. To improve the energy conversion efficiency of the TEG, a fuzzy logic controller (FLC)-based perturb & observe (P&O) type maximum power point tracking (MPPT) control algorithm is used in this study. An EWH is one of the major electricity consuming household appliances which causes a higher electricity price for consumers. Also, a significant amount of thermal energy… More >