Topic Editors

School of Engineering, University of Portsmouth, Anglesea Building, Anglesea Road, Portsmouth, PO1 3DJ, UK
Laboratory of Innovative Technologies, University of Picardie Jules Verne, 80025 Amiens, France

Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume

Abstract submission deadline
31 October 2024
Manuscript submission deadline
31 December 2024
Viewed by
16192

Topic Information

Dear Colleagues,

This Topic is a continuation of the previous successful Topic “Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems”.

The electrical power system is undergoing a revolution enabled by advances in telecommunications, computer hardware and software, measurement and metering systems, IoT, and power electronics. The increasing integration of intermittent renewable energy sources, energy storage devices, electric vehicles, and the drive for energy efficiency have resulted in an evolution of the traditional power systems towards a smarter grid, which is characterised, in part, by a bidirectional flow of energy and information. The evolution of the power grid, as well as its interconnection with energy storage systems and renewable energy sources, has created new opportunities for optimising not only its techno-economic aspects at the planning stages but also its control and operation. However, new challenges are emerging in optimising these systems related to the complexity, the uncertainties involved, and the nonlinear dynamic behaviour that these systems exhibit.

We are pleased to invite prospective authors to submit original research submissions covering innovations associated with the optimisation and optimal control in electrical power, energy storage and renewable energy systems, and the challenges associated with their nonlinear, uncertain, and complex behaviour. Topics of interest include but are not limited to:

  • Novel approaches for the optimisation of techno-economic aspects of electrical power, energy storage, or renewable energy systems at the planning stage;
  • Nonlinear dynamics in electrical power, energy storage, or renewable energy systems;
  • Nonlinear and optimal control approaches for microgrids, energy storage, or the integration of renewable energy systems into the power grid;
  • Revenue maximisation of energy storage systems;
  • Nonlinear state estimation for electrical power, energy storage, or renewable energy systems;
  • Optimal power flow with energy storage and/or renewable energy sources.

Prof. Dr. Victor M. Becerra
Prof. Dr. Ahmed Rachid
Topic Editors

Keywords

  • optimal control
  • nonlinear dynamics
  • optimization
  • nonlinear systems
  • nonlinear control
  • power systems
  • energy storage systems
  • renewable energy systems
  • renewable energy integration
  • smart grids
  • microgrids
  • electric vehicles
  • battery systems

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Energies
energies
3.2 5.5 2008 16.1 Days CHF 2600 Submit
Processes
processes
3.5 4.7 2013 13.7 Days CHF 2400 Submit
Electronics
electronics
2.9 4.7 2012 15.6 Days CHF 2400 Submit
Batteries
batteries
4.0 5.4 2015 17.7 Days CHF 2700 Submit
Electricity
electricity
- - 2020 20.3 Days CHF 1000 Submit

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Published Papers (12 papers)

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26 pages, 2508 KiB  
Article
Determining Fast Battery Charging Profiles Using an Equivalent Circuit Model and a Direct Optimal Control Approach
by Julio Gonzalez-Saenz and Victor Becerra
Energies 2024, 17(6), 1470; https://doi.org/10.3390/en17061470 - 19 Mar 2024
Viewed by 451
Abstract
This work used an electrical equivalent circuit model combined with a temperature model and computational optimal control methods to determine minimum time charging profiles for a lithium–ion battery. To effectively address the problem, an optimal control problem formulation and direct solution approach were [...] Read more.
This work used an electrical equivalent circuit model combined with a temperature model and computational optimal control methods to determine minimum time charging profiles for a lithium–ion battery. To effectively address the problem, an optimal control problem formulation and direct solution approach were adopted. The results showed that, in most cases studied, the solution to the battery’s fast-charging problem resembled the constant current–constant voltage (CC-CV) charging protocol, with the advantage being that our proposed approach optimally determined the switching time between the CC and CV phases, as well as the final time of the charging process. Considering path constraints related to the terminal voltage and temperature gradient between the cell core and case, the results also showed that additional rules could be incorporated into the protocol to protect the battery against under/over voltage-related damage and high-temperature differences between the core and its case. This work addressed several challenges and knowledge gaps, including emulating the CC-CV protocol using a multi-phase optimal control approach and direct collocation methods, and improving it by including efficiency and degradation terms in the objective function and safety constraints. To the authors’ knowledge, this is the first time the CC-CV protocol has been represented as the solution to a multi-phase optimal control problem. Full article
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19 pages, 3594 KiB  
Article
Energy Storage Dynamic Configuration of Active Distribution Networks—Joint Planning of Grid Structures
by Yiming Luo, Peigen Tian, Xin Yan, Xi Xiao, Song Ci, Qi Zhou and Yi Yang
Processes 2024, 12(1), 79; https://doi.org/10.3390/pr12010079 - 28 Dec 2023
Viewed by 586
Abstract
The integration of distributed power generation mainly consisting of photovoltaic and wind power into active distribution networks can lead to safety accidents in grid operation. At the same time, climate change can also cause voltage fluctuations, direct current injection, harmonic pollution, frequency fluctuations, [...] Read more.
The integration of distributed power generation mainly consisting of photovoltaic and wind power into active distribution networks can lead to safety accidents in grid operation. At the same time, climate change can also cause voltage fluctuations, direct current injection, harmonic pollution, frequency fluctuations, and other issues. To achieve economic and safe operation of the distribution network, an active distribution network-network planning model considering the dynamic configuration of energy storage system energy storage is constructed. This model focuses on energy storage batteries with high ease of use, high modularity, and strong mobility. The route location planning involving different load operating scenarios in spring, summer, autumn, and winter is constructed. The objective function includes the revenue from selling electricity in the distribution network, the expenditure on purchasing electricity in the distribution network, and the cost during the planned construction period. The constraints include three major constraints: distribution network operation, network topology, and energy storage system operation. Three numerical examples are set up to analyze the impact of energy storage system dynamic configuration on grid planning. The results confirmed the active distribution network-grid planning model for dynamic configuration of energy storage systems. Both Example 2 and Example 3 had 3 ESS configurations. Case 3 showed different access methods for ESS in different seasons. The access nodes for ESS in spring and winter were 4, 5, and 6, while the access nodes for summer and autumn were 3, 5, and 6. After applying the proposed method, the daily energy storage investment of commercial, residential, and industrial users gradually stabilized. The reliability of electricity consumption was improved, with an improvement rate of about 40%. The research has brought considerable economic benefits to distribution network operators. It has forward-looking academic value in the joint planning of grid structures and energy storage. Full article
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32 pages, 8697 KiB  
Article
Energy Conversion Optimization Method in Nano-Grids Using Variable Supply Voltage Adjustment Strategy Based on a Novel Inverse Maximum Power Point Tracking Technique (iMPPT)
by Lucian Nicolae Pintilie, Horia Cornel Hedeșiu, Călin Gheorghe Rusu, Petre Dorel Teodosescu, Călin Ignat Mărginean, Sorin Ionuț Salcu, Vasile Mihai Suciu, Norbert Csaba Szekely and Alexandru Mădălin Păcuraru
Electricity 2023, 4(4), 277-308; https://doi.org/10.3390/electricity4040017 - 10 Oct 2023
Viewed by 1212
Abstract
This paper introduces a novel power supply voltage adjustment strategy that can determine the optimum voltage value based on the amount of absorbed power. The novel automatic voltage adjustment technique was called inverse maximum power point tracking (iMPPT). The proposed control strategy consists [...] Read more.
This paper introduces a novel power supply voltage adjustment strategy that can determine the optimum voltage value based on the amount of absorbed power. The novel automatic voltage adjustment technique was called inverse maximum power point tracking (iMPPT). The proposed control strategy consists of a modified maximum power point tracking (MPPT) algorithm (more precisely the P&O method). In this case, the modified MPPT technique establishes the minimum value of the input absorbed power of a consumer load served by a switched-mode power supply (SMPS). The iMPPT adjusts the input power by modifying the input voltage of the main power supply. The served loads are connected to the variable power supply via an interfacing power electronics converter that performs the automatic voltage regulation function (AVR). The optimal value of the input voltage level can be achieved when the input power of the automatic voltage regulation converter is at a minimum. In that case, the energy conversion efficiency ratio is at a maximum, and the overall losses related to the front-end power stage are at a minimum. The proposed technique can also be considered a Maximum Efficiency Tracking (MET) method. By performing the inverse operation of a maximum power point tracking algorithm on the input demanded power of a switched mode power supply (SMPS), the optimum input voltage level can be determined when the maximum energy conversion ratio (related to a given load level) is achieved. The novel proposed iMPPT method can improve the energy conversion ratio from 85% up to approximately 10% in the case of an output power level of 800 W served by a synchronous buck converter at the input voltage level of 350 V. The total amount of recovered power in this situation can be approximately 100 W. Full article
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12 pages, 4135 KiB  
Article
Research on Coordinated Control Strategy of DFIG-ES System Based on Fuzzy Control
by Jianghong Chen, Teng Yuan, Xuelian Li, Weiliang Li and Ximu Wang
Energies 2023, 16(12), 4770; https://doi.org/10.3390/en16124770 - 16 Jun 2023
Cited by 2 | Viewed by 764
Abstract
As the penetration rate of wind power systems is rising, which causes the overall system’s inertia to decline, the power system’s capacity to regulate frequency will be negatively affected. Therefore, this paper investigates the inertia control of doubly fed induction generation, and an [...] Read more.
As the penetration rate of wind power systems is rising, which causes the overall system’s inertia to decline, the power system’s capacity to regulate frequency will be negatively affected. Therefore, this paper investigates the inertia control of doubly fed induction generation, and an energy storage system is installed in the wind farm to respond to the frequency deviation. First, a fuzzy control-based virtual inertia adaptive control strategy is presented. The goal of dynamic adjustment of the virtual inertia coefficient is realized by taking into account the uncertain factors of wind speed and frequency change rate. A recovery strategy based on the energy storage system’s level of charge is employed to prevent overcharging and over-discharging of the battery. Then, a weight factor based on frequency deviation is introduced to combine the droop output of the energy storage system with the virtual inertia output of the doubly fed induction generation, and the joint output mode of the wind storage system is determined in each stage of primary frequency regulation. Finally, the simulation verification is performed using the wind storage system simulation model created by MATLAB. The comparison results with other control methods prove that the proposed method is effective. Full article
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28 pages, 14851 KiB  
Article
IMODBO for Optimal Dynamic Reconfiguration in Active Distribution Networks
by Naiwei Tu and Zuhao Fan
Processes 2023, 11(6), 1827; https://doi.org/10.3390/pr11061827 - 15 Jun 2023
Cited by 3 | Viewed by 969
Abstract
A dynamic reconfiguration method based on the improved multi-objective dung beetle optimizer (IMODBO) is proposed to reduce the operating cost of the distribution network with distributed generation (DG) and ensure the quality of the power supply, while also minimizing the number of switch [...] Read more.
A dynamic reconfiguration method based on the improved multi-objective dung beetle optimizer (IMODBO) is proposed to reduce the operating cost of the distribution network with distributed generation (DG) and ensure the quality of the power supply, while also minimizing the number of switch operations during dynamic reconfiguration. First, a multi-objective model of distribution network dynamic reconfiguration with the optimization goal of minimizing active power loss and voltage deviation is established. Secondly, the K-means++ clustering algorithm is used to divide the daily load of the distribution network into periods. Finally, using the IMODBO algorithm, the distribution network is reconstructed into a single period. The IMODBO algorithm uses the chaotic tent map to initialize the population, which increases the ergodicity of the initial population and solves the problem of insufficient search space. The algorithm introduces an adaptive weight factor to solve the problem of the algorithm easily falling into a locally optimal solution in the early stage with weak searchability in the later stage. Levy flight is introduced in the perturbation strategy, and a variable spiral search strategy improves the search range and convergence accuracy of the dung beetle optimizer. Reconfiguration experiments on the proposed method were conducted using a standard distribution network system with distributed power generation. Multiple sets of comparative experiments were carried out on the IEEE 33-nodes and PG&E 69-nodes. The results demonstrated the effectiveness of the proposed method in addressing the multi-objective distribution network dynamic reconfiguration problem. Full article
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14 pages, 2334 KiB  
Article
Diminishing Active Power Loss and Improving Voltage Profile Using an Improved Pathfinder Algorithm Based on Inertia Weight
by Samson Ademola Adegoke and Yanxia Sun
Energies 2023, 16(3), 1270; https://doi.org/10.3390/en16031270 - 25 Jan 2023
Cited by 4 | Viewed by 1299
Abstract
Part of the widely discussed problem in electrical power systems is the optimal reactive power dispatch (ORPD) due to its reliability and economical operation of electrical power systems. The ORPD is a complex and nonlinear optimization problem. The pathfinder algorithm (PFA) is a [...] Read more.
Part of the widely discussed problem in electrical power systems is the optimal reactive power dispatch (ORPD) due to its reliability and economical operation of electrical power systems. The ORPD is a complex and nonlinear optimization problem. The pathfinder algorithm (PFA) is a newly developed algorithm that inspires the group movement of prey with a leader called a pathfinder when hunting for food. The inertia weight is added to the PFA and is called an improved pathfinder algorithm (IPFA) to support the proper random work of the swarm to avoid the decrease in searchability of the PFA. The IPFA was proposed in this work to diminish the active power loss while improving the voltage profile. The IPFA was validated on the IEEE 30 and 118 bus systems along with particle swarm optimization (PSO) and the teaching–learning-based optimizer (TLBO). The proposed IPFA provides the best result as the losses of the IEEE 30 and 118 test systems were reduced to 16.035 and 115.048 MW from the initial base of 17.89 and 132.86 MW, respectively. The losses of PSO and the TLBO were 16.1568 and 16.1607 MW for the IEEE 30 bus system, respectively, while for the IEEE 118 bus system, the PSO provided 117.9129 MW and the TLBO provided 118.0524 MW. The two test systems’ reduction percentages (%) were 10.37% and 13.41%, respectively. The results were compared with those of other algorithms in the literature, and the IPFA provided a superior result, thereby suggesting the superiority of IPFA methods in diminishing the power loss and improving the system’s voltage profile. Full article
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14 pages, 473 KiB  
Article
Solar Energy and Biomass within Distributed Generation for a Northeast Brazil Hotel
by Karollyne Marques de Lima, Danielle Bandeira de Mello Delgado, Dener Delmiro Martins and Monica Carvalho
Energies 2022, 15(23), 9170; https://doi.org/10.3390/en15239170 - 03 Dec 2022
Cited by 1 | Viewed by 1635
Abstract
Besides satisfying the energy demands of buildings, distributed generation can contribute toward environmental conservation. However, determining the best configuration and operational strategy for these systems is a complex task due to the available technology options and the dynamic operating conditions of buildings and [...] Read more.
Besides satisfying the energy demands of buildings, distributed generation can contribute toward environmental conservation. However, determining the best configuration and operational strategy for these systems is a complex task due to the available technology options and the dynamic operating conditions of buildings and their surroundings. This work addressed the synthesis and optimization of an energy system for a commercial building (hotel). Electricity, hot water, and cooling demands were established for a hotel located in Northeast Brazil. The optimization problem was based on mixed-integer linear programming and included conventional equipment, solar energy resource (photovoltaic and thermal technologies), and biomass. The objective function of the optimization was to minimize annual economic costs, which involved considering the capital and operation costs. A reference system was established for comparison purposes, where energy demands were met conventionally (without cogeneration or renewable energy), whose annual cost was BRL 80,799. Although the optimal solution did not rely on cogeneration, it benefited from the high degree of energy integration and had a total annual cost of BRL 24,358 (70% lower). The optimal solution suggested the installation of 70 photovoltaic panels and used biomass (sugarcane bagasse) to operate a hot water boiler. Solar collectors for hot water production were not part of the optimal solution. Sensitivity analyses were also carried out, varying the electricity and natural gas tariffs, and the type of biomass employed, but the configuration of the system did not change compared with the optimal economic solution. Full article
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14 pages, 1961 KiB  
Article
Numerical and Experimental Study of a PVT Water System under Daily Weather Conditions
by Talha Batuhan Korkut, Aytaç Gören and Ahmed Rachid
Energies 2022, 15(18), 6538; https://doi.org/10.3390/en15186538 - 07 Sep 2022
Cited by 3 | Viewed by 1829
Abstract
Worldwide need for renewable energy sources increases significantly with the drastic negative greenhouse effects of climate change. This study considers a water-cooled hybrid thermo-electric panel (PV/T) which contributes to better harvesting of solar energy. A numerical CFD model was developed for power generation [...] Read more.
Worldwide need for renewable energy sources increases significantly with the drastic negative greenhouse effects of climate change. This study considers a water-cooled hybrid thermo-electric panel (PV/T) which contributes to better harvesting of solar energy. A numerical CFD model was developed for power generation of a standard PV panel as well as for a water-based PV/T system laminated with polymer matrix composite (PMC) materials, and user-defined functions (UDFs) were developed and integrated with the CFD model to implement exact boundary conditions. Experimentation under daily weather conditions was carried out in order to validate the numerical CFD model by measuring the surface temperatures of PV and PV/T systems as well as the temperatures of the water inlet and outlet of the cooling system. The results show that the maximum and minimum deviations of the surface temperature between numerical and experimental studies matched well compared with the studies performed in the literature. Moreover, the numerical model had a rapid response to temperature changes of PV and PV/T modules under sudden weather changes (cloudy/sunny). It was shown that the electrical efficiency of the cooled PV/T module can achieve 20.8% in addition to a thermal efficiency of 53.5%. The current study is a validation of the performance of polymer composite laminated water-cooled PV/T systems under daily weather conditions. Full article
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19 pages, 688 KiB  
Article
Effective Fault Detection and Diagnosis for Power Converters in Wind Turbine Systems Using KPCA-Based BiLSTM
by Zahra Yahyaoui, Mansour Hajji, Majdi Mansouri, Kamaleldin Abodayeh, Kais Bouzrara and Hazem Nounou
Energies 2022, 15(17), 6127; https://doi.org/10.3390/en15176127 - 23 Aug 2022
Cited by 8 | Viewed by 1872
Abstract
The current work presents an effective fault detection and diagnosis (FDD) technique in wind energy converter (WEC) systems. The proposed FDD framework merges the benefits of kernel principal component analysis (KPCA) model and the bidirectional long short-term memory (BiLSTM) classifier. In the developed [...] Read more.
The current work presents an effective fault detection and diagnosis (FDD) technique in wind energy converter (WEC) systems. The proposed FDD framework merges the benefits of kernel principal component analysis (KPCA) model and the bidirectional long short-term memory (BiLSTM) classifier. In the developed FDD approach, the KPCA model is applied to extract and select the most effective features, while the BiLSTM is utilized for classification purposes. The developed KPCA-based BiLSTM approach involves two main steps: feature extraction and selection, and fault classification. The KPCA model is developed in order to select and extract the most efficient features and the final features are fed to the BiLSTM to distinguish between different working modes. Different simulation scenarios are considered in this study in order to show the robustness and performance of the developed technique when compared to the conventional FDD methods. To evaluate the effectiveness of the proposed KPCA-based BiLSTM approach, we utilize data obtained from a healthy WTC, which are then injected with several fault scenarios: simple fault generator-side, simple fault grid-side, multiple fault generator-side, multiple fault grid-side, and mixed fault on both sides. The diagnosis performance is analyzed in terms of accuracy, recall, precision, and computation time. Furthermore, the efficiency of fault diagnosis is shown by the classification accuracy parameter. The experimental results show the efficiency of the developed KPCA-based BiLSTM technique compared to the classical FDD techniques (an accuracy of 97.30%). Full article
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16 pages, 4564 KiB  
Article
Fault Detecting and Isolating Schemes in a Low-Voltage DC Microgrid Network from a Remote Village
by Pascal Hategekimana, Adria Junyent Ferre, Joan Marc Rodriguez Bernuz and Etienne Ntagwirumugara
Energies 2022, 15(12), 4460; https://doi.org/10.3390/en15124460 - 19 Jun 2022
Cited by 8 | Viewed by 1982
Abstract
Fault detection and isolation are important tasks to improve the protection system of low voltage direct current (LVDC) networks. Nowadays, there are challenges related to the protection strategies in the LVDC systems. In this paper, two proposed methods for fault detection and isolation [...] Read more.
Fault detection and isolation are important tasks to improve the protection system of low voltage direct current (LVDC) networks. Nowadays, there are challenges related to the protection strategies in the LVDC systems. In this paper, two proposed methods for fault detection and isolation of the faulty segment through the line and bus voltage measurement were discussed. The impacts of grid fault current and the characteristics of protective devices under pre-fault normal, under-fault, and post-fault conditions were also discussed. It was found that within a short time after fault occurrence in the network, this fault was quickly detected and the faulty line segment was efficiently isolated from the grid, where this grid was restored to its normal operating conditions. For analysing the fault occurrence and its isolation, two algorithms with their corresponding MATLAB/SIMULINK platforms were developed. The findings of this paper showed that the proposed methods would be used for microgrid protection by successfully resolving the fault detection and grid restoration problems in the LVDC microgrids, especially in rural villages. Full article
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15 pages, 1902 KiB  
Article
High-Performance Fractional Order PIMR-Type Repetitive Control for a Grid-Tied Inverter
by Jun Yu, Qiangsong Zhao, Hengyi Li, Xuebin Yue and Shengjun Wen
Energies 2022, 15(11), 3854; https://doi.org/10.3390/en15113854 - 24 May 2022
Cited by 1 | Viewed by 1135
Abstract
Low switching frequency is usually used in high-power wind grid-tied inverter systems to reduce power loss caused by on–off switching activity. Proportional integral multi-resonant type repetitive control (PIMR-type RC) can track reference grid current signals and suppress harmonic signals of grid-tied inverter system. [...] Read more.
Low switching frequency is usually used in high-power wind grid-tied inverter systems to reduce power loss caused by on–off switching activity. Proportional integral multi-resonant type repetitive control (PIMR-type RC) can track reference grid current signals and suppress harmonic signals of grid-tied inverter system. A low switching frequency will result in a low sampling rate of control system. However, integer-order phase-lead compensation will lead to a poor compensation accuracy of PIMR-type RC with a low sampling rate, leading to poor tracking and suppressing performance of PIMR-type RC, and even result in system instability. To solve these problems, a high-performance fractional-order phase-lead compensation PIMR-type RC (FO-PIMR-RC) scheme is proposed in this paper. Fractional-order phase-lead compensation is adopted to compensate accurately the phase lag caused by controlled plant and PIMR-type RC and approximately realized by a finite impulse response (FIR) filter. Stability analysis and harmonic suppression performance are provided, and the parameter optimization design is implemented. Simulation and experimental results prove the desirable performance of the proposed control scheme. Full article
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26 pages, 4502 KiB  
Article
Decentralized Coordination Dispatch Model Based on Chaotic Mutation Harris Hawks Optimization Algorithm
by Yuanyuan Wang, Zexu Yu, Zhenhai Dou, Mengmeng Qiao, Ye Zhao, Ruishuo Xie and Lianxin Liu
Energies 2022, 15(10), 3815; https://doi.org/10.3390/en15103815 - 22 May 2022
Cited by 3 | Viewed by 1279
Abstract
Aiming at the economic dispatch problem for an interconnected system with wind power integration, and in order to realize the goals of system economy and improvement of the cross-regional consumption level of wind energy, a decentralized coordination dispatch model is established in this [...] Read more.
Aiming at the economic dispatch problem for an interconnected system with wind power integration, and in order to realize the goals of system economy and improvement of the cross-regional consumption level of wind energy, a decentralized coordination dispatch model is established in this paper. In this model, a DC tie-line is cut by the branch cutting method and used as a coupling variable. A virtual upper-level dispatch center is established, and the economic dispatch problem to be solved is decomposed into a master optimization problem for the upper-level dispatch center and subsidiary optimization problems for the lower-level dispatch centers. For solving this model, an improved Harris hawks optimization (HHO) algorithm called the chaotic mutation Harris hawks optimization (CMHHO) algorithm is proposed. In the CMHHO algorithm, tent mapping and the “DE/pbad-to-pbest/1” strategy are introduced, and a new nonlinear escape energy factor adjustment is proposed. Through an algorithm comparison experiment and a simulation experiment with two examples, the superiority of the CMHHO algorithm, the effectiveness of the proposed model and the applicability of the CMHHO algorithm to the proposed model are verified. The model proposed is of great significance for solving the economic dispatch problem for an interconnected system with wind power integration. Full article
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