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Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 16432

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Special Issue Editors

Prof. Dr. Chaoshun Li

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School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: modeling; simulation and optimal control of hydropower; wind and photovoltaic power generation systems; power generation equipment status monitoring; fault diagnosis and health management; new energy power system dispatch; microgrid energy management and control; big data; deep learning and artificial intelligence application research

Prof. Dr. Yun Zeng

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Guest Editor

Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650031, China
Interests: the control of hydro turbine generating units control and nonlinear control theory application

Dr. Beibei Xu

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Guest Editor

Department of Agricultural Hydraulic Engineering, Northwest A&F University, Xianyang, China
Interests: wind/solar/pumped storage system; hybrid energy systems; load flexibility; risk assessment; optimizes power supply
Special Issues, Collections and Topics in MDPI journals

Dr. Dong Liu

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Guest Editor

School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: refined modeling; stability analysis; adaptive control; optimal operation and fault diagnosis of hydro-turbine regulation system for conventional hydropower station or pumped storage station

Special Issue Information

Dear Colleagues,

The modeling and optimal control of renewable energy sources such as hydraulic, wind and photovoltaic, which play an increasing role in modern power systems, are of great importance for safe and stable system operation. Renewable energy systems are a class of complex nonlinear systems with a random and intermittent nature, time-varying parameter characteristics, and non-minimum phase characteristics. Traditional models are far from accurate in describing complex systems and have no advantage in large-scale energy optimization design, so it is crucial to establish higher-accuracy renewable energy system models for mechanism and application research. At the same time, due to the coupling of several physical factors in energy systems, a combination of multiple modeling approaches is required to realize multi-field coupled simulation, which is, undoubtedly, a great challenge. On the other hand, the complexity and variability of the structure and composition of power systems make the operating conditions and production environment for renewable energy generation systems subject to many uncertainties, and the traditional PID control strategy has been difficult to adapt to this new normal. Therefore, it is time to innovate the control mode of renewable energy units to make the regulation more intelligent, efficient and reliable, which is also an important guarantee of whether renewable energy generation systems can replace traditional energy on a large scale in the future.

This Special Issue aims to present and disseminate the most recent advances related to the theory and/or application research on the modeling and optimal operation of hydraulic, wind and photovoltaic power generation systems. All submissions within the scope of the listed keywords are welcome.

The topics of interest for publication include, but are not limited to, the keywords below.

Prof. Dr. Chaoshun Li
Prof. Dr. Yun Zeng
Dr. Beibei Xu
Dr. Dong Liu
Guest Editors

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Keywords

hydraulic power generation system
solar power generation system
photovoltaic power generation system
system integration
refined modeling
optimal operation
advanced/intelligent control
cooperative control
performance evaluation
scheduling and planning
fault forecasting/diagnosis
CFD simulation
1D–3D coupling simulation
multi-energy complementary
stability analysis
100% renewable power system
smart microgrid

Published Papers (11 papers)

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Research

13 pages, 3535 KiB

Open AccessArticle

A 1D-3D Coupling Model to Evaluate Hydropower Generation System Stability

by Meng Zhang, Jinhai Feng, Ziwen Zhao, Wei Zhang, Junzhi Zhang and Beibei Xu

Energies 2022, 15(19), 7089; https://doi.org/10.3390/en15197089 - 27 Sep 2022

Cited by 1 | Viewed by 931

Abstract

This paper proposes a novel 1D-3D approach for the stability characteristics of the hydropower generation system (HGS) in transition processes. First, a 1D-3D coupling model was established for the HGS in the load-reduction process. Second, a sensitivity analysis of the HGS’s parameters to the rotation speed and discharge was conducted. Third, the pressure pulsation characteristics of the HGS with three typical guide vane openings were analyzed during the load-reduction process. The results show that with the closure of the guide vane, the discharge gradually decreases and it is sensitive to the change in hydraulic parameters. The rotation speed fluctuates at the early stage of the transition process and is easily affected by mechanical parameters. In addition, the pressure pulsation inside the Francis turbine is more intense under small openings than large openings, and the primary frequency of pressure pulsation under three opening degrees is the blade frequency. The 1D-3D coupling model successfully integrates the advantages of traditional methods and provides a reference for predicting system stability and exploring the stability mechanism. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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26 pages, 5001 KiB

Open AccessArticle

Degradation Trend Prediction of Hydropower Units Based on a Comprehensive Deterioration Index and LSTM

by Yunhe Wang, Zhihuai Xiao, Dong Liu, Jinbao Chen, Dong Liu and Xiao Hu

Energies 2022, 15(17), 6273; https://doi.org/10.3390/en15176273 - 28 Aug 2022

Cited by 4 | Viewed by 1222

Abstract

Deterioration trend prediction of hydropower units helps to detect abnormal conditions of hydropower units and can prevent early failures. The reliability and accuracy of the prediction results are crucial to ensure the safe operation of the units and promote the stable operation of the power system. In this paper, the long short-term neural network (LSTM) is introduced, a comprehensive deterioration index (CDI) trend prediction model based on the time–frequency domain is proposed, and the prediction accuracy of the situation trend of hydropower units is improved. Firstly, the time–domain health model (THM) is constructed with back-propagation neural network (BPNN) and condition parameters of active power, guide vane opening and blade opening and the time–domain indicators. Subsequently, a frequency-domain health model (FHM) is established based on ensemble empirical mode decomposition (EEMD), approximate entropy (ApEn), and k-means clustering algorithm. Later, the time–domain degradation index (TDI) is developed according to THM, the frequency-domain degradation index (FDI) is constructed according to FHM, and the CDI is calculated as a weighted sum by TDI and FDI. Finally, the prediction model of LSTM is proposed based on the CDI to achieve degradation trend prediction. In order to validate the effectiveness of the CDI and the accuracy of the prediction model, the vibration waveform dataset of a hydropower plant in China is taken as a case study and compared with four different prediction models. The results demonstrate that the proposed model outperforms other comparison models in terms of predicting accuracy and stability. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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19 pages, 7223 KiB

Open AccessArticle

Dynamic Characteristics and Successive Start-Up Control Strategy Optimization of Pumped Storage Units under Low-Head Extreme Conditions

by Yonggang Li, Jinjiao Hou, Juan Gu, Chaoshun Li and Yanhe Xu

Energies 2022, 15(15), 5428; https://doi.org/10.3390/en15155428 - 27 Jul 2022

Cited by 1 | Viewed by 1011

Abstract

With inherent ‘S’ characteristics and the one-tunnel-with-two-units arrangement of the pump-turbine, hydraulic transient changes in the successive start-up process are complex, and the optimal control is difficult. This paper aims to study the dynamic characteristics and successive start-up control strategy optimization of two hydraulic couplings pumped storage units (PSUs) under low-head extreme conditions. Firstly, an accurate model of two hydraulic coupling PSUs’ successive start-up is established. Based on this model, the influence of the interval time of successive start-up on the dynamic characteristics of PSUs is carried out. It is shown that the change of the interval time of the successive start-up (ΔT) of the two PSUs has a significant impact on the dynamic response stability of the low-head start-up. If ΔT is more than 40 s, the hydraulic oscillation and speed fluctuation of the PSUs deteriorate. Secondly, with the different controller parameters for the two PSUs, a novel multi-objective optimization scheme with fractional order PID controller (FOPID) is proposed to figure out the best control scheme for the successive start-up. Furthermore, selecting the sum of the rise time (T_r) of the rotating speed of two PSUs and the sum of the integral time absolute error (ITAE) of two PSUs is the objective. Meanwhile, the optimization scheme of PID with different parameters (PIDDP) is used to compare and verify the optimization method proposed in this paper. The results for this extreme condition indicate that FOPID has more significant advantages in optimizing the instability of the successive start-up process, with the better Pareto front, and the optimized scheme has a more stable dynamic transition process of flow, water hammer pressure, and rotational speed. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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24 pages, 5412 KiB

Open AccessArticle

Nonlinear Modeling and Stability of a Doubly-Fed Variable Speed Pumped Storage Power Station with Surge Tank Considering Nonlinear Pump Turbine Characteristics

by Nan Zhang, Xiaoming Xue, Na Sun, Yanhui Gu, Wei Jiang and Chaoshun Li

Energies 2022, 15(11), 4131; https://doi.org/10.3390/en15114131 - 04 Jun 2022

Cited by 5 | Viewed by 1339

Abstract

This paper investigates the nonlinear modeling and stability of a doubly-fed variable speed pumped storage power station (DFVSPSPS). Firstly, the mathematical model of DFVSPSPS with surge tank considering nonlinear pump turbine characteristics was derived and established. Then, Hopf bifurcation analysis of DFVSPSPS was performed. The stable region was identified and verified by example analysis. Moreover, the effect mechanism of nonlinear pump turbine characteristics on the stability of DFVSPSPS was explored. Finally, the influence of factors on the stability and dynamic response of DFVSPSPS was studied. The results indicate that the emerged Hopf bifurcation of DFVSPSPS is supercritical and the region on the low side of the bifurcation line is the stable region. Nonlinear head characteristics have a significant influence on the stability and dynamic response of DFVSPSPS. Nonlinear speed characteristics have an obvious effect on the stability and dynamic response of DFVSPSPS only under positive load disturbance and unstable surge tank. Nonlinear head characteristics are unfavorable for the stability of DFVSPSPS under positive load disturbance and favorable under negative load disturbance. A smaller flow inertia of penstock, a smaller head loss of penstock and a greater unit inertia time constant are favorable for the stability of DFVSPSPS. The stable region under the positive disturbance of active power is larger than that under the negative disturbance of active power. The time constant of the surge tank presents a saturation characteristic on the stability of DFVSPSPS. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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11 pages, 1618 KiB

Open AccessArticle

Impacts of Yield and Seasonal Prices on the Operation of Lancang Cascaded Reservoirs

by Mengfei Xie, Suzhen Feng, Jinwen Wang, Maolin Zhang and Cheng Chen

Energies 2022, 15(9), 3247; https://doi.org/10.3390/en15093247 - 28 Apr 2022

Cited by 1 | Viewed by 909

Abstract

This work formulates a stochastic dynamic programming (SDP) model that incorporates seasonal electricity prices and can handle a constraint on power yield, which is assumed to be satisfied at any time it is possible, thus allowing for an analysis of their impacts on the operational performances of cascaded reservoirs. The model is applied to the Lancang Cascade, specifically its two largest reservoirs, Xiaowan and Nuozhadu. The results show that increasing the power yield of the cascade will reduce energy production unfavorably but will impact water spillage favorably, with a power yield of 2000 MW and with a 91% reliability suggested as being a satisfactory operational target. The case study also suggests that using seasonal electricity prices makes the power generation very unstable during weeks 12–20, which is a period of time that is critical to transferring from dry to flooding seasons. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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15 pages, 3081 KiB

Open AccessArticle

Research on the Operational Strategy of the Hybrid Wind/PV/Small-Hydropower/Facility-Agriculture System Based on a Microgrid

by Yan Ren, Linmao Ren, Kai Zhang, Dong Liu, Xianhe Yao and Huawei Li

Energies 2022, 15(7), 2466; https://doi.org/10.3390/en15072466 - 27 Mar 2022

Cited by 4 | Viewed by 1716

Abstract

The use of renewable energy sources, such as wind, photovoltaics (PV), and hydropower, to supply facility agriculture may effectively mitigate food and environmental pollution problems and ensure continuity of the energy supply. The operating conditions of a hybrid system are complex, so the operating strategy is very important for system configuration and scheduling purposes. In the current study, first, a hybrid wind/PV/small-hydropower/facility-agricultural system was constructed. Then, the chaotic particle swarm method was applied to optimize hybrid system operation, and a scheduling strategy of the hybrid system was proposed. Finally, combined with an example, according to wind and PV power output and load curves, supply-to-load curves for wind, PV, and small hydropower were obtained. The operational strategy proposed in this study maximizes the utilization of wind and solar resources and rationally allocates hydropower resources. The aforementioned operational strategy provides a basis for hybrid system capacity allocation and scheduling. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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18 pages, 6387 KiB

Open AccessArticle

Noise Reduction Study of Pressure Pulsation in Pumped Storage Units Based on Sparrow Optimization VMD Combined with SVD

by Yan Ren, Linlin Zhang, Jiangtao Chen, Jinwei Liu, Pan Liu, Ruoyu Qiao, Xianhe Yao, Shangchen Hou, Xiaokai Li, Chunyong Cao and Hongping Chen

Energies 2022, 15(6), 2073; https://doi.org/10.3390/en15062073 - 11 Mar 2022

Cited by 3 | Viewed by 1868

Abstract

The unbalanced forces generated by pumped storage units operating under non-ideal operating conditions can cause pressure pulsations. Due to the noise interference, the feature information reflecting the operating state of the unit in the pressure pulsation is difficult to extract. Therefore, this paper proposes a noise reduction method based on sparrow search algorithm (SSA) optimized variational mode decomposition (VMD) combined with singular value decomposition (SVD). Firstly, SSA is used to realize the adaptive optimization of VMD parameters for ideal decomposition of the signal. Then, the noise reduction of the decomposed signal is performed by using the sensitivity of the Permutation Entropy (PE) for small mutations. The noise reduction and reconstruction of the decomposed signal are carried out again by using SVD. The experimental and comparison results show that the mean square error of the signal after VMD-SVD feature extraction is reduced from 1.0068 to 0.0732 and the correlation coefficient is increased from 0.2428 to 0.9614. It is proved that the method achieves better results in the pressure pulsation signal of pumped storage units and has some application significance for the fault diagnosis of pumped storage units. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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15 pages, 5916 KiB

Open AccessArticle

Research on Thermodynamic Characteristics of Hydraulic Power Take-Off System in Wave Energy Converter

by Yubo Niu, Xingyuan Gu, Xuhui Yue, Yang Zheng, Peijie He and Qijuan Chen

Energies 2022, 15(4), 1373; https://doi.org/10.3390/en15041373 - 14 Feb 2022

Viewed by 1267

Abstract

Hydraulic power-take-off (PTO) systems which utilize high-pressure oil circuits to transmit energy are widely applied in wave energy generation. The properties of hydraulic oil are significantly influenced by environmental conditions, and its dynamic viscosity is sensitive to temperature, especially in relatively low-temperature cases. This paper studies the characteristics of the hydraulic PTO when started in different temperature conditions via numerical analysis and experimental verification. An improved numerical model of the hydraulic PTO system is proposed, in which the effects of temperature on the hydraulic oil viscosity and hydraulic motor efficiency are quantitatively investigated, and consequently, the thermal-hydraulic characteristics can be sufficiently considered. The performances of the hydraulic PTO in start-up processes with different initial temperatures and in long term operation are assessed. The results show that the presented model can reasonably describe the hydraulic PTO characteristics. The efficiency of hydraulic PTO degrades when it starts at low temperatures. The efficiency increases in relatively high temperature, while larger fluctuations of the flow rate and output power are observed. This study can provide guidance for enhancing the efficiency and consistency of hydraulic PTO operating in actual sea conditions. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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13 pages, 3932 KiB

Open AccessArticle

Piecewise Causality Study between Power Load and Vibration in Hydro-Turbine Generator Unit for a Low-Carbon Era

by Lianda Duan, Dekuan Wang, Guiping Wang, Changlin Han, Weijun Zhang, Xiaobo Liu, Cong Wang, Zheng Che and Chang Chen

Energies 2022, 15(3), 1207; https://doi.org/10.3390/en15031207 - 07 Feb 2022

Cited by 2 | Viewed by 1428

Abstract

With the rapid development of wind and photovoltaic power generation, hydro-turbine generator units have to operate in a challenging way, resulting in obvious vibration problems. Because of the significant impact of vibration on safety and economical operation, it is of great significance to study the causal relationship between vibration and other variables. The complexity of the hydro-turbine generator unit makes it difficult to analyze the causality of the mechanism. This paper studied the correlation based on a data-driven method, then transformed the correlation into causality based on the mechanism. In terms of correlation, traditional research only judges whether there is a correlation between all data. When the data with correlation are interfered with by the data without correlation, the traditional methods cannot accurately identify the correlation. A piecewise correlation method based on change point detection was proposed to fill this research gap. The proposed method segmented time series pairs, then analyzed the correlation between subsequences. The causality between power load and vibration of a hydro-turbine generator unit was further analyzed. It indicated that when the power load is less than 200 MW, the causality is weak, and when the power load is greater than 375 MW, the causality is strong. The results show that the causality between vibration and power load is not fixed but piecewise. Furthermore, the piecewise correlation method compensated for the limitation of high variance of the maximum information coefficient. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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21 pages, 6472 KiB

Open AccessArticle

Degradation Trend Prediction of Pumped Storage Unit Based on MIC-LGBM and VMD-GRU Combined Model

by Peng Chen, Yumin Deng, Xuegui Zhang, Li Ma, Yaoliang Yan, Yifan Wu and Chaoshun Li

Energies 2022, 15(2), 605; https://doi.org/10.3390/en15020605 - 15 Jan 2022

Cited by 6 | Viewed by 1971

Abstract

The harsh operating environment aggravates the degradation of pumped storage units (PSUs). Degradation trend prediction (DTP) provides important support for the condition-based maintenance of PSUs. However, the complexity of the performance degradation index (PDI) sequence poses a severe challenge of the reliability of DTP. Additionally, the accuracy of healthy model is often ignored, resulting in an unconvincing PDI. To solve these problems, a combined DTP model that integrates the maximal information coefficient (MIC), light gradient boosting machine (LGBM), variational mode decomposition (VMD) and gated recurrent unit (GRU) is proposed. Firstly, MIC-LGBM is utilized to generate a high-precision healthy model. MIC is applied to select the working parameters with the most relevance, then the LGBM is utilized to construct the healthy model. Afterwards, a performance degradation index (PDI) is generated based on the LGBM healthy model and monitoring data. Finally, the VMD-GRU prediction model is designed to achieve precise DTP under the complex PDI sequence. The proposed model is verified by applying it to a PSU located in Zhejiang province, China. The results reveal that the proposed model achieves the highest precision healthy model and the best prediction performance compared with other comparative models. The absolute average (

| A V G |

) and standard deviation (

S T D

) of fitting errors are reduced to 0.0275 and 0.9245, and the RMSE, MAE, and

R^{2}

are 0.00395, 0.0032, and 0.9226 respectively, on average for two operating conditions. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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19 pages, 9999 KiB

Open AccessArticle

Hopf Bifurcation and Parameter Sensitivity Analysis of a Doubly-Fed Variable-Speed Pumped Storage Unit

by Zhiwei Zhu, Xiaoqiang Tan, Xueding Lu, Dong Liu and Chaoshun Li

Energies 2022, 15(1), 204; https://doi.org/10.3390/en15010204 - 29 Dec 2021

Cited by 7 | Viewed by 1485

Abstract

The doubly-fed variable speed pumped storage unit is a storage system suitable for joint operation with renewable energy sources to smooth the imbalance between renewable energy supply and electricity demand. However, its working principle and operation control are more complex than those of constant speed pumped storage. In this study, a nonlinear model of doubly-fed variable speed pumped storage units (VSPSUs) considering nonlinear characteristics of the head loss is established. The study finds that a supercritical Hopf bifurcation occurs in the system, and the area enclosed by the lower side of the bifurcation line and the coordinate axis is the stability domain of the system. The active power step perturbation from −0.3 to 0.3 will gradually reduce the area of the stability domain and narrow the adjustable range of the control parameters. In addition, the sensitivity of the model full state variables and the primary and secondary relationships to the changes of subsystem parameters is analyzed systematically using the trajectory sensitivity. It is found that there is a large difference in the sensitivity of different state variables to the parameters. The state variables are much more sensitive to the transfer coefficient of hydraulic turbine torque to guide vane opening, the unit inertia time constant, and the controller proportional gain change than other parameters, which are defined as highly sensitive parameters. The receiver response time constant and the turbine flow-to-head transfer coefficient are the corresponding low-sensitivity parameters. Full article

(This article belongs to the Special Issue Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems)

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