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  • Open Access


    Artificial Neural Network-Based Development of an Efficient Energy Management Strategy for Office Building

    Payal Soni, J. Subhashini*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1225-1242, 2023, DOI:10.32604/iasc.2023.038155

    Abstract In the current context, a smart grid has replaced the conventional grid through intelligent energy management, integration of renewable energy sources (RES) and two-way communication infrastructures from power generation to distribution. Energy management from the distribution side is a critical problem for balancing load demand. A unique energy management strategy (EMS) is being developed for office building equipment. That includes renewable energy integration, automation, and control based on the Artificial Neural Network (ANN) system using Matlab Simulink. This strategy reduces electric power consumption and balances the load demand of the traditional grid. This strategy is developed by taking inputs from… More >

  • Open Access


    Research on Multi-Objective Optimization Model of Industrial Microgrid Considering Demand Response Technology and User Satisfaction

    Junhui Li1,*, Jinxin Zhong1, Kailiang Wang1, Yu Luo1, Qian Han2, Jieren Tan2

    Energy Engineering, Vol.120, No.4, pp. 869-884, 2023, DOI:10.32604/ee.2023.021320

    Abstract In the process of wind power, coal power, and energy storage equipment participating in the operation of industrial microgrids, the stable operation of wind-storage industrial microgrids is guaranteed by considering demand response technology and user satisfaction. This paper firstly sorts out the status quo of microgrid operation optimization, and determines the main requirements for user satisfaction considering three types of load characteristics, demand response technology, power consumption benefit loss, user balance power purchase price and wind power consumption evaluation indicators in the system. Secondly, the operation architecture of the windstorage industrial microgrid is designed, and the multi-objective optimization model of… More >

  • Open Access


    Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

    Song Zhang1, Wensheng Li2, Zhao Li2, Xiaolei Zhang1, Zhipeng Lu1, Xiaoning Ge3,*

    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 the uncertainty of renewables. In… More >

  • Open Access


    Management of Peak Loads in an Emerging Electricity Market

    Edwin N. Mbinkar1,*, Derek Ajesam Asoh1,2,3, Jerome Ndam Mungwe3, Livinus Songyuh4, Emmanuel Lamfu5

    Energy Engineering, Vol.119, No.6, pp. 2637-2654, 2022, DOI:10.32604/ee.2022.023419

    Abstract An electricity market is a trading platform provided by the actors in the electricity sector to sell and buy electricity while maintaining the stability of the transmission network and minimizing energy losses. The management of electrical energy for rational use consists of all the operations that the consumers can carry out in order to minimize their electricity bill, while the producers optimize their benefits and the transmission infrastructure. The reduction of active and reactive power consumption and the smoothing of daily and yearly load profiles are the main objectives in this work. Many developed countries already have properly functioning electricity… More > Graphic Abstract

    Management of Peak Loads in an Emerging Electricity Market

  • Open Access


    Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

    Rongxin Zhang1,*, Chengying Yang2,3, Xuetao Li1

    Energy Engineering, Vol.119, No.6, pp. 2489-2511, 2022, DOI:10.32604/ee.2022.021517

    Abstract Buildings are the main energy consumers across the world, especially in urban communities. Building smartization, or the smartification of housing, therefore, is a major step towards energy grid smartization too. By controlling the energy consumption of lighting, heating, and cooling systems, energy consumption can be optimized. All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources (RES), which mitigates environmental impacts and reduces peak demand for electrical energy. In this paper, a new optimization algorithm is applied to solve the optimal energy consumption problem by considering the electric vehicles and demand… More >

  • Open Access


    Bio-Inspired Optimal Dispatching of Wind Power Consumption Considering Multi-Time Scale Demand Response and High-Energy Load Participation

    Peng Zhao1, Yongxin Zhang1, Qiaozhi Hua2,*, Haipeng Li3, Zheng Wen4

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 957-979, 2023, DOI:10.32604/cmes.2022.021783

    Abstract Bio-inspired computer modelling brings solutions from the living phenomena or biological systems to engineering domains. To overcome the obstruction problem of large-scale wind power consumption in Northwest China, this paper constructs a bio-inspired computer model. It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load. First, the principle of wind power obstruction with the involvement of a high-energy load is examined in this work. In this step, highenergy load model with different regulation characteristics is established. Then, considering the multi-time scale characteristics of high-energy load and other demand-side… More >

  • Open Access


    Real-Time Demand Response Management for Controlling Load Using Deep Reinforcement Learning

    Yongjiang Zhao, Jae Hung Yoo, Chang Gyoon Lim*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5671-5686, 2022, DOI:10.32604/cmc.2022.027443

    Abstract With the rapid economic growth and improved living standards, electricity has become an indispensable energy source in our lives. Therefore, the stability of the grid power supply and the conservation of electricity is critical. The following are some of the problems facing now: 1) During the peak power consumption period, it will pose a threat to the power grid. Enhancing and improving the power distribution infrastructure requires high maintenance costs. 2) The user's electricity schedule is unreasonable due to personal behavior, which will cause a waste of electricity. Controlling load as a vital part of incentive demand response (DR) can… More >

  • Open Access


    Investigating the Effects of the Driving Cycle and Penetration of Electric Vehicles on Technical and Environmental Characteristics of the Hybrid Energy System Considering Uncertainties

    Jiusong Chen1,*, Dejun Miao1, Yizong Dai1, Mojtaba Ghadamyari2,*

    Energy Engineering, Vol.119, No.5, pp. 1985-2003, 2022, DOI:10.32604/ee.2022.021142

    Abstract Electric vehicles (EVs) have received special consideration from modern society over the past several years. Although EVs are a fine example of environmentally friendly technology and have many advantages, they relatively increase the electricity demand upon a power grid as well. Therefore, their negative impact on busvoltage and line losses should be analyzed. In this study, the effect of EV loads and their penetration on bus voltage and line losses of an IEEE-33 bussystem has been examined via two scenarios. It is important to mention that the effect of EVs on the rate of air pollution, produced by fossil fuel… More >

  • Open Access


    Economic Analysis of Demand Response Incorporated Optimal Power Flow

    Ulagammai Meyyappan*, S. Joyal Isac

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

    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 pricing, time of use, and… More >

  • Open Access


    Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response

    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 response, wind and photovoltaic curtailment,… More >

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