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  • Open Access

    ARTICLE

    Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

    Zhishuo Zhang, Xinhui Du*, Yaoke Shang, Jingshu Zhang, Wei Zhao, Jia Su

    Energy Engineering, Vol.121, No.6, pp. 1577-1605, 2024, DOI:10.32604/ee.2024.047706

    Abstract To address the issues of limited demand response data, low generalization of demand response potential evaluation, and poor demand response effect, the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis. Firstly, based on the demand response process and demand response behavior, obtain demand response characteristics that characterize the process and behavior. Secondly, establish a feature extraction and prediction model based on data mining, including similar day clustering,… More >

  • Open Access

    ARTICLE

    A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

    Hao Qi1, Mohamed Sharaf2, Andres Annuk3, Adrian Ilinca4, Mohamed A. Mohamed5,*

    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 >

  • Open Access

    ARTICLE

    Research on Operation Optimization of Energy Storage Power Station and Integrated Energy Microgrid Alliance Based on Stackelberg Game

    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

    Research on Operation Optimization of Energy Storage Power Station and Integrated Energy Microgrid Alliance Based on Stackelberg Game

  • Open Access

    ARTICLE

    A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

    Wenlu Ji*, Teng Tu, Nan Ma

    Energy Engineering, Vol.121, No.5, pp. 1223-1243, 2024, DOI:10.32604/ee.2024.046112

    Abstract To improve the resilience of a distribution system against extreme weather, a fuel-based distributed generator (DG) allocation model is proposed in this study. In this model, the DGs are placed at the planning stage. When an extreme event occurs, the controllable generators form temporary microgrids (MGs) to restore the load maximally. Simultaneously, a demand response program (DRP) mitigates the imbalance between the power supply and demand during extreme events. To cope with the fault uncertainty, a robust optimization (RO) method is applied to reduce the long-term investment and short-term operation costs. The optimization is formulated More >

  • Open Access

    ARTICLE

    Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

    Mousumi Basu1, Chitralekha Jena2, Baseem Khan3,4,*, 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 More >

  • Open Access

    ARTICLE

    Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

    Jun Zhao*, Chaoying Yang, Ran Li, Jinge Song

    Energy Engineering, Vol.121, No.3, pp. 747-767, 2024, DOI:10.32604/ee.2023.042806

    Abstract Due to the impact of source-load prediction power errors and uncertainties, the actual operation of the park will have a wide range of fluctuations compared with the expected state, resulting in its inability to achieve the expected economy. This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control (MPC). In the day-ahead stage, an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time More >

  • Open Access

    ARTICLE

    Peak Shaving Strategy of Concentrating Solar Power Generation Based on Multi-Time-Scale and Considering Demand Response

    Lei Fang*, Haiying Dong, Xiaofei Zhen, Shuaibing Li

    Energy Engineering, Vol.121, No.3, pp. 661-679, 2024, DOI:10.32604/ee.2023.029823

    Abstract According to the multi-time-scale characteristics of power generation and demand-side response (DR) resources, as well as the improvement of prediction accuracy along with the approaching operating point, a rolling peak shaving optimization model consisting of three different time scales has been proposed. The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination, generation power, and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full… More >

  • Open Access

    ARTICLE

    Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

    Lifeng Wang1, Jing Yu2,*, Wenlu Ji1

    Energy Engineering, Vol.121, No.2, pp. 523-540, 2024, DOI:10.32604/ee.2023.041881

    Abstract Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users, the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies. For this purpose, a power grid-flexible load bilevel model is constructed based on dynamic pricing, where the leader is the dispatching center and the lower-level flexible load acts as the follower. Initially, an upper-level day-ahead dispatching model for… More >

  • Open Access

    ARTICLE

    Electricity-Carbon Interactive Optimal Dispatch of Multi-Virtual Power Plant Considering Integrated Demand Response

    Shiwei Su1,2, Guangyong Hu2, Xianghua Li3, Xin Li2, Wei Xiong2,*

    Energy Engineering, Vol.120, No.10, pp. 2343-2368, 2023, DOI:10.32604/ee.2023.028500

    Abstract As new power systems and dual carbon policies develop, virtual power plant cluster (VPPC) provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems. To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant, a multi-virtual power plant (VPP) electricity-carbon interaction optimal scheduling model considering integrated demand response (IDR) is proposed. Firstly, a multi-VPP electricity-carbon interaction framework is established. The interaction of electric energy and carbon quotas can realize energy complementarity, reduce energy waste and promote low-carbon operation. Secondly, in order to coordinate the… More > Graphic Abstract

    Electricity-Carbon Interactive Optimal Dispatch of Multi-Virtual Power Plant Considering Integrated Demand Response

  • Open Access

    ARTICLE

    Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

    Hassan Shokouhandeh1, Mehrdad Ahmadi Kamarposhti2,*, William Holderbaum3, Ilhami Colak4, Phatiphat Thounthong5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 809-822, 2023, DOI:10.32604/csse.2023.035827

    Abstract The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the… More >

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