Zhan Shi^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 973-994, 2024, DOI:10.32604/cmc.2024.051530

Abstract The convergence of Internet of Things (IoT), 5G, and cloud collaboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data processing. While generative adversarial networks (GANs) are instrumental in resource scheduling, their application in this domain is impeded by challenges such as convergence speed, inferior optimality searching capability, and the inability to learn from failed decision making feedbacks. Therefore, a cloud-edge collaborative federated GAN-based communication and computing resource scheduling algorithm with long-term constraint violation sensitiveness is proposed to address these challenges. The proposed algorithm facilitates real-time, energy-efficient data processing by More >

Hao Qi¹, Mohamed Sharaf², Andres Annuk³, Adrian Ilinca⁴, Mohamed A. Mohamed^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1387-1404, 2024, DOI:10.32604/cmes.2024.048672

Abstract Hot dry rock (HDR) is rich in reserve, widely distributed, green, low-carbon, and has broad development potential and prospects. In this paper, a distributionally robust optimization (DRO) scheduling model for a regionally integrated energy system (RIES) considering HDR co-generation is proposed. First, the HDR-enhanced geothermal system (HDR-EGS) is introduced into the RIES. HDR-EGS realizes the thermoelectric decoupling of combined heat and power (CHP) through coordinated operation with the regional power grid and the regional heat grid, which enhances the system wind power (WP) feed-in space. Secondly, peak-hour loads are shifted using price demand response guidance More >

Yu Zhang^*, Lianmin Li, Zhongxiang Liu, Yuhu Wu

Energy Engineering, Vol.121, No.5, pp. 1209-1221, 2024, DOI:10.32604/ee.2024.046141

Abstract With the development of renewable energy technologies such as photovoltaics and wind power, it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage. To solve the problem of the interests of different subjects in the operation of the energy storage power stations (ESS) and the integrated energy multi-microgrid alliance (IEMA), this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game. In the upper layer, ESS optimizes charging and discharging decisions More > Graphic Abstract

Ming Li^1,*, Rifucairen Fu¹, Tuerhong Yaxiaer¹, Yunping Zheng¹, Abiao Huang², Ronghui Liu², Shunfu Lin²

Energy Engineering, Vol.121, No.2, pp. 405-424, 2024, DOI:10.32604/ee.2023.044509

Abstract From the perspective of a community energy operator, a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads. The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system (IES) before and after; the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme, taking into account the fluctuation of wind turbine output and load within a short period of time and according to 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… More >

Enhui Sun^1,2, Jiahao Shi^1,2, Lei Zhang^1,2,*, Hongfu Ji^1,2, Qian Zhang^1,2, Yongyi Li^1,2

Energy Engineering, Vol.120, No.7, pp. 1583-1602, 2023, DOI:10.32604/ee.2023.027790

Abstract This paper studies the feasibility of a supply-side wind-coal integrated energy system. Based on grid-side data, the load regulation model of coal-fired power and the wind-coal integrated energy system model are established. According to the simulation results, the reasons why the wind-coal combined power supply is difficult to meet the grid-side demand are revealed through scenario analysis. Based on the wind-coal combined operation, a wind-coal-storage integrated energy system was proposed by adding lithium-iron phosphate battery energy storage system (LIPBESS) to adjust the load of the system. According to the four load adjustment scenarios of grid-side… More >

Song Zhang¹, Wensheng Li², Zhao Li², Xiaolei Zhang¹, Zhipeng Lu¹, Xiaoning Ge^3,*

Energy Engineering, Vol.120, No.1, pp. 181-199, 2023, DOI:10.32604/ee.2022.022228

Abstract Driven by the goal of “carbon neutrality” and “emission peak”, effectively controlling system carbon emissions has become significantly important to governments around the world. To this end, a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response (IDR) is proposed in this paper for the integrated energy system (IES), where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR. In contrast, the second stage minimizes the system total cost to optimize the outputs of generations with consideration of More >

Zhukui Tan^1,*, Yongjie Ren¹, Hua Li¹, Weili Ren², Xichao Zhou², Ming Zeng¹

Energy Engineering, Vol.119, No.6, pp. 2607-2619, 2022, DOI:10.32604/ee.2022.019550

Abstract With the proposal of carbon neutrality, how to improve the proportion of clean energy in energy consumption and reduce carbon dioxide emissions has become the important challenge for the traditional energy industry. Based on the idea of multi-energy complementarity, a typical integrated energy system consisting of electric system and gas system is constructed based on the application of power to gas (P2G) technology and gas turbine in this paper. Furthermore, a multi-objective optimization model with economic improvement, carbon emission reduction and peak-load shifting as objectives is proposed, and solved by BSO algorithm. Finally, a typical More >

Qidai Lin¹, Ying Gong^2,*, Yizhi Shi¹, Changsen Feng², Youbing Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 929-944, 2022, DOI:10.32604/cmes.2022.020752

Abstract The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multi-energy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated… More >

Jian Dong, Haixin Wang, Junyou Yang^*, Liu Gao, Kang Wang, Xiran Zhou

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 319-340, 2022, DOI:10.32604/cmes.2022.020394

Abstract Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy. This paper studies an electric-gas-heat integrated energy system, including the carbon capture system, energy coupling equipment, and renewable energy. An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost, carbon emission and enhance the power supply reliability. Firstly, the low-carbon mathematical model of combined thermal and power unit, carbon capture system and power to gas unit (CCP) is established. Subsequently, we establish a low carbon multi-objective optimization model considering system operation cost, carbon emissions cost, integrated demand More >