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

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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

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Energies energies	3.0	6.2	2008	17.5 Days	CHF 2600	Submit
Processes processes	2.8	5.1	2013	14.4 Days	CHF 2400	Submit
Electronics electronics	2.6	5.3	2012	16.8 Days	CHF 2400	Submit
Batteries batteries	4.6	4.0	2015	22 Days	CHF 2700	Submit
Electricity electricity	-	4.8	2020	27.2 Days	CHF 1000	Submit

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Published Papers (19 papers)

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30 pages, 3414 KiB  

Open AccessArticle

The Calibrated Safety Constraints Optimal Power Flow for the Operation of Wind-Integrated Power Systems

by Kai-Hung Lu, Wenjun Qian, Yuesong Jiang and Yi-Shun Zhong

Processes 2024, 12(10), 2272; https://doi.org/10.3390/pr12102272 - 17 Oct 2024

Viewed by 462

Abstract

As the penetration of renewable energy sources (RESs), particularly wind power, continues to rise, the uncertainty in power systems increases. This challenges traditional optimal power flow (OPF) methods. This paper proposes a Calibrated Safety Constraints Optimal Power Flow (CSCOPF) model that uses the [...] Read more.

As the penetration of renewable energy sources (RESs), particularly wind power, continues to rise, the uncertainty in power systems increases. This challenges traditional optimal power flow (OPF) methods. This paper proposes a Calibrated Safety Constraints Optimal Power Flow (CSCOPF) model that uses the Improved Acceleration Coefficient-Based Bee Swarm algorithm (IACBS) in combination with the equivalent current injection (ECI) model. The proposed method addresses key challenges in wind-integrated power systems by ensuring preventive safety scheduling and enabling effective power incident safety analysis (PISA). This improves system reliability and stability. This method incorporates mixed-integer programming, with continuous and discrete variables representing power outputs and control mechanisms. Detailed numerical simulations were conducted on the IEEE 30-bus test system, and the feasibility of the proposed method was further validated on the IEEE 118-bus test system. The results show that the IACBS algorithm outperforms the existing methods in both computational efficiency and robustness. It achieves lower generation costs and faster convergence times. Additionally, the CSCOPF model effectively prevents power grid disruptions during critical incidents, ensuring that wind farms remain operational within predefined safety limits, even in fault scenarios. These findings suggest that the CSCOPF model provides a reliable solution for optimizing power flow in renewable energy-integrated systems, significantly contributing to grid stability and operational safety. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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22 pages, 8025 KiB  

Open AccessFeature PaperArticle

A Novel VSG with Adaptive Virtual Inertia and Adaptive Damping Coefficient to Improve Transient Frequency Response of Microgrids

by Erico Gurski, Roman Kuiava, Filipe Perez, Raphael A. S. Benedito and Gilney Damm

Energies 2024, 17(17), 4370; https://doi.org/10.3390/en17174370 - 1 Sep 2024

Viewed by 772

Abstract

This paper proposes a combined adaptive virtual Inertia and adaptive damping control of a virtual synchronous generator (AID-VSG) to improve the dynamic frequency response of microgrids. In the proposed control scheme, the VSG’s virtual inertia and damping coefficients adapt themselves during the transients [...] Read more.

This paper proposes a combined adaptive virtual Inertia and adaptive damping control of a virtual synchronous generator (AID-VSG) to improve the dynamic frequency response of microgrids. In the proposed control scheme, the VSG’s virtual inertia and damping coefficients adapt themselves during the transients to, respectively, reduce frequency deviations and increase the oscillations’ damping. In addition, as an important feature, the proposed AID-VSG is suitable for distributed control scheme applications and is designed to not rely on phase-locked loop (PLL) measurements, which avoids PLL stability issues on weak grids. The control parameters of the proposed AID-VSG are tuned by the particle swarm optimization (PSO) algorithm to minimize the overshoot and settling time of the microgrid’s frequency during an islanding event. The AID-VSG is validated by a comparative analysis with three existing VSG control schemes, also tuned by the stated optimization algorithm. The performance of each compared VSG strategy is evaluated through the simulation of a set of 10,000 initial conditions, using the islanded microgrid’s nonlinear model. The best response among the VSG strategies was achieved by the proposed AID-VSG control for both the optimization problem and the set of initial conditions’ simulations. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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16 pages, 939 KiB  

Open AccessArticle

State-of-Charge and State-of-Health Estimation in Li-Ion Batteries Using Cascade Electrochemical Model-Based Sliding-Mode Observers

by Yong Feng, Chen Xue, Fengling Han, Zhenwei Cao and Rebecca Jing Yang

Batteries 2024, 10(8), 290; https://doi.org/10.3390/batteries10080290 - 15 Aug 2024

Viewed by 858

Abstract

This paper proposes a cascade approach based on a sliding mode observer (SMO) for estimating the state of charge (SoC) and state of health (SoH) of lithium-ion (Li-ion) batteries using a single particle model (SPM). After convergence, the observation error signal of the [...] Read more.

This paper proposes a cascade approach based on a sliding mode observer (SMO) for estimating the state of charge (SoC) and state of health (SoH) of lithium-ion (Li-ion) batteries using a single particle model (SPM). After convergence, the observation error signal of the current node in the cascade observer is generated from the output injection signal of the previous node’s observer. The current node’s observer generates its output injection signal, leading to its convergence. This sequential process accurately determines the observed values of each node using only the battery’s current and voltage. Subsequently, the SoC and SoH are estimated using observations of lithium-ion concentrations on the surface and inside the battery anode. The accuracy of this approach is validated using Dynamic Stress Test (DST) and Federal Urban Driving Scheme (FUDS) experimental data. A comparative analysis with conventional SMO and Extended Kalman Filter (EKF) algorithms demonstrates the approach’s effectiveness and superior performance, confirming its practical applicability. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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27 pages, 3962 KiB  

Open AccessArticle

Cost-Effective Planning of Hybrid Energy Systems Using Improved Horse Herd Optimizer and Cloud Theory under Uncertainty

by Ali S. Alghamdi

Electronics 2024, 13(13), 2471; https://doi.org/10.3390/electronics13132471 - 24 Jun 2024

Viewed by 836

Abstract

In this paper, an intelligent stochastic model is recommended for the optimization of a hybrid system that encompasses wind energy sources, battery storage, combined heat and power generation, and thermal energy storage (Wind/Battery/CHP/TES), with the inclusion of electric and thermal storages through the [...] Read more.

In this paper, an intelligent stochastic model is recommended for the optimization of a hybrid system that encompasses wind energy sources, battery storage, combined heat and power generation, and thermal energy storage (Wind/Battery/CHP/TES), with the inclusion of electric and thermal storages through the cloud theory model. The framework aims to minimize the costs of planning, such as construction, maintenance, operation, and environmental pollution costs, to determine the best configuration of the resources and storage units to ensure efficient electricity and heat supply simultaneously. A novel meta-heuristic optimization algorithm named improved horse herd optimizer (IHHO) is applied to find the decision variables. Rosenbrock’s direct rotational technique is applied to the conventional horse herd optimizer (HHO) to improve the algorithm’s performance against premature convergence in the optimization due to the complexity of the problem, and its capability is evaluated with particle swarm optimization (PSO) and manta ray foraging optimization (MRFO) methods. Also, the cloud theory-based stochastic model is recommended for solving problems with uncertainties of system generation and demand. The obtained results are evaluated in three simulation scenarios including (1) Wind/Battery, (2) Wind/Battery/CHP, and (3) Wind/Battery/CHP/TES systems to implement the proposed methodology and evaluate its effectiveness. The results show that scenario 3 is the best configuration to meet electrical and thermal loads, with the lowest planning cost (12.98% less than scenario 1). Also, the superiority of the IHHO is proven with more accurate answers and higher convergence rates in contrast to the conventional HHO, PSO, and MRFO. Moreover, the results show that when considering the cloud theory-based stochastic model, the costs of annual planning are increased for scenarios 1 to 3 by 4.00%, 4.20%, and 3.96%, respectively, compared to the deterministic model. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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18 pages, 6452 KiB  

Open AccessArticle

VSG Frequency Response Strategy for Doubly-Fed Wind Farm Considering the Fatigue Load

by Ruichao Cui, Hanbo Wang, Yingming Liu, Xiaodong Wang and Panpan Zhang

Electronics 2024, 13(12), 2310; https://doi.org/10.3390/electronics13122310 - 13 Jun 2024

Viewed by 524

Abstract

A wind farm composed of doubly-fed wind turbines (DFWTs) based on the virtual synchronous generator (DFWTs-VSG) control strategy exacerbates the fatigue load on the main shaft of the DFWT-VSGs in the wind farm when responding to the frequency variation of the power system. [...] Read more.

A wind farm composed of doubly-fed wind turbines (DFWTs) based on the virtual synchronous generator (DFWTs-VSG) control strategy exacerbates the fatigue load on the main shaft of the DFWT-VSGs in the wind farm when responding to the frequency variation of the power system. The central controller of the wind farm can reduce the main shaft fatigue load of each DFWT-VSG by reasonably allocating the required damping coefficient of each DFWT-VSG while engaging in power system frequency response. In this study, a damping coefficient allocation method considering the main shaft fatigue load is proposed. First, a discretization equation that quantifies the relationship between the damping coefficient and its main shaft torque in DFWT-VSG is constructed. Then, based on this discretization equation, the minimization of the sum of main shaft torque fluctuation from all DFWT-VSGs is taken as the objective function in the central controller, and the constraints of the damping coefficient are set based on the support capacity of the wind farm and the operating state of each DFWT-VSG. Finally, the required damping coefficient of each DFWT-VSG is allocated in real-time based on the fmincon algorithm in the central controller. Simulation results verify the superiority of the proposed damping coefficient allocation method. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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22 pages, 4678 KiB  

Open AccessArticle

Optimal Dispatching of Microgrids with Development of Prosumers Sharing Energy Storage

by Fei Li, Kai Su, Xianshan Li and Binqiao Zhang

Electronics 2024, 13(10), 1899; https://doi.org/10.3390/electronics13101899 - 12 May 2024

Viewed by 1013

Abstract

The charge/discharge operation of the prosumer’s energy storage and the energy interaction between prosumers and MGs are chaotic from the overall point of the MG’s operation. It causes considerable resource waste and reduces the overall benefits of the MG with multi-prosumers. Therefore, a [...] Read more.

The charge/discharge operation of the prosumer’s energy storage and the energy interaction between prosumers and MGs are chaotic from the overall point of the MG’s operation. It causes considerable resource waste and reduces the overall benefits of the MG with multi-prosumers. Therefore, a game theory-based optimal scheduling strategy for the MG with multi-prosumers combined into a PRCO is proposed in this paper. According to the prosumers’ complementary characteristics of ES utilization and energy production, prosumers can be integrated into the PRCO to obtain energy reciprocity by sharing ES with an ordered charge–discharge operation. Meanwhile, to improve the collaboration of prosumers and the overall efficiency of the MG, a game scheduling model is established with the MG as the leader and the PRCO as the follower. The ToU price incentive policy is implemented in the MG to maximize the operational benefits and reduce the difference between the valley and peak load. Meanwhile, the PRCO responds to the price policy and implements an ordered charge–discharge strategy of ES to optimize each member’s energy scheduling strategy and minimize the total costs. The PRCO revenues are distributed to prosumers based on the Shapley value method. The uniqueness and existence of Stackelberg equilibrium in the game model are proved. The simulations of a community MG show that the ordered charge–discharge operation of ES is achieved and the overall benefits of the system are improved. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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22 pages, 4989 KiB  

Open AccessArticle

Electro-Hydraulic Servo-Pumped Active Disturbance Rejection Control in Wind Turbines for Enhanced Safety and Accuracy

by Tiangui Zhang, Haohui Yu, Bo Yu, Chao Ai, Xiaoxiang Lou, Pengjie Xiang, Ruilin Li and Jianchen Li

Processes 2024, 12(5), 908; https://doi.org/10.3390/pr12050908 - 29 Apr 2024

Viewed by 906

Abstract

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to [...] Read more.

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b₀ (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b₀ is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability. Full article

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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26 pages, 2508 KiB  

Open AccessFeature PaperArticle

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

Cited by 2 | Viewed by 1150

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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19 pages, 3594 KiB  

Open AccessArticle

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

Cited by 2 | Viewed by 1048

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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32 pages, 8697 KiB  

Open AccessArticle

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 1656

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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12 pages, 4135 KiB  

Open AccessArticle

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 4 | Viewed by 1060

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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28 pages, 14851 KiB  

Open AccessArticle

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 7 | Viewed by 1479

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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14 pages, 2334 KiB  

Open AccessArticle

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 5 | Viewed by 1816

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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14 pages, 473 KiB  

Open AccessArticle

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 - 3 Dec 2022

Cited by 2 | Viewed by 2076

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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14 pages, 1961 KiB  

Open AccessArticle

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 - 7 Sep 2022

Cited by 7 | Viewed by 2582

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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19 pages, 688 KiB  

Open AccessArticle

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 14 | Viewed by 2381

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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16 pages, 4564 KiB  

Open AccessArticle

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 10 | Viewed by 2520

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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15 pages, 1902 KiB  

Open AccessArticle

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 1432

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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26 pages, 4502 KiB  

Open AccessArticle

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 1610

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

(This article belongs to the Topic Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems, 2nd Volume)

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