Wind-solar Complementary Power Research Articles

Optimal Design of Wind-Solar complementary power generation systems considering the maximum capacity of renewable energy

This paper proposes constructing a multi-energy complementary power generation system integrating hydropower, wind, and solar energy. Considering capacity configuration and optimization of the complementary power generation system, a dual-layer planning model is constructed. The outer layer aims to maximize the accessible scale of wind and solar energy, while the inner layer considers the matching degree between power output and grid load. The optimization uses a particle swarm algorithm to obtain wind and solar energy integration's optimal ratio and capacity configuration. The results indicate that a wind-solar ratio of around 1.25:1, with wind power installed capacity of 2350 MW and photovoltaic installed capacity of 1898 MW, results in maximum wind and solar installed capacity. Furthermore, installed capacity increases with increasing wind and solar curtailment rates and loss-of-load probabilities. When the loss-of-load probability is set to 3 %, the impact of wind and solar curtailment rates on the installed capacity ratio is relatively small. The complementary characteristics of wind and solar energy can be fully utilized, which better aligns with fluctuations in user loads, promoting the integration of wind and solar resources and ensuring the safe and stable operation of the system.

Design of a Seawater Desalination System with Two-Stage Humidification and Dehumidification Desalination Driven by Wind and Solar Energy

The paper presents a wind–photovoltaic-thermal hybrid-driven two-stage humidification and dehumidification desalination system for remote island regions lacking access to electricity and freshwater resources. By conducting an analysis of the wind and solar energy resources at the experimental site, a suitable wind power station and photovoltaic power station are constructed. The performance of the wind–solar complementary power generation system is then evaluated based on factors such as output power, seawater desalination load power, battery compensation output, system energy consumption, and water production costs. A variable step gradient disturbance method based on the power–duty ratio is proposed for tracking the maximum power point (MPPT) of wind power generation. The output power of the photovoltaic power generation system is optimized, employing a fuzzy logic control (FLC) method to track the MPPT of photovoltaic power generation. This approach effectively addresses the issues of slow speed and low accuracy encountered by traditional MPPT algorithms in tracking the maximum power point (MPP) of both photovoltaic and wind power generations. In order to ensure that the desalination system can operate stably under different weather conditions, eight working modes are designed, and a programmable logic controller (PLC) is used to control the system, which provides a guarantee for stable water production. Experimental results demonstrate that the system exhibits stable performance, achieving a maximum water output of 80.63 Kg/h and daily water yield is 751.32 Kg, the cost of desalination equipment is 1.4892 USD/t.

Achieving wind power and photovoltaic power prediction: An intelligent prediction system based on a deep learning approach

Accurately predicting wind and photovoltaic power is one of the keys to improving the economy of wind-solar complementary power generation system, reducing scheduling costs and no-load losses, and ensuring grid stability. However, the natural properties of energy result in complex fluctuations in their corresponding power sequences, making accurate predictions difficult. Therefore, this paper proposes an intelligent prediction system that combines decomposition algorithms and deep learning for ultra-short-term prediction of wind and photovoltaic power. First, an improved decomposition algorithm is proposed, based on fuzzy entropy's property that its value increases with the increase of sequence uncertainty, particle swarm optimization (PSO) is used to search for the optimal parameter combinations of variational modal decomposition (VMD), so that it can automatically adjust the parameters for energy data with different characteristics to reduce the human error. Then, a convolutional neural network (CNN) architecture that balances operational efficiency and prediction performance is constructed, and the hyperparameters of the CNN are optimized using the wild horse optimization algorithm (WHO) to improve the stability and accuracy of the prediction model. In this paper, real data from wind power plants and photovoltaic power plants in China are used as experimental objects, and experiments are carried out in three aspects, namely, benchmark model selection, decomposition algorithm comparison and combined model comparison. The results show that selecting CNN as the benchmark model is a good choice; the improved VMD has better decomposition performance than other state-of-the-art decomposition algorithms. The system proposed in this paper is highly generalizable and adaptive, and its prediction performance and accuracy greatly outperform that of other comparative models, with prediction accuracies improved by 72% and 79%, respectively, compared to a single CNN model.

Stochastic Energy Management Strategy of Smart Building Microgrid with Electric Vehicles and Wind-Solar Complementary Power Generation System

Stochastic Energy Management Strategy of Smart Building Microgrid with Electric Vehicles and Wind-Solar Complementary Power Generation System

Simulation of Wind-solar Complementary Distribution Power Generation System Based on PSCAD

Toward to the situation that the overall model and simulation research ofcomplementary power generation system is less recently, a new structuremodel of the wind-solar complementary distribution power generation sys-tem is proposed. According to the models of wind power generation andphotovoltaic power generation, the PSCAD is used for building a three-phasephotovoltaic grid-connected power generation system. Through the model,the systm performance is analyzed, and the correctness of the developedcontrol element and the usability of the engineering simulation analysis areverified.

Multivariate analysis and optimal configuration of wind-photovoltaic complementary power generation system

Advantages of wind-solar complementary power generation system to utilize solar and wind energy in the aspect of resource and technical economy have been reviewed tersely. Convenience of entering and exiting generating equipment and load from DC as well as AC bus are interpreted briefly. The factors that affect the electrical power output of the system were analyzed and studied. Based on the law of energy conservation, the energetic matching algorithm was proposed which forms the foundation of optimal configuration of system. Finally, the intelligent control and on-line monitoring of wind-solar complementary power generation system were discussed.

Research on security monitoring system for wind-solar complementary power generation based on internet of things

Research on security monitoring system for wind-solar complementary power generation based on internet of things

Research on security monitoring system for wind-solar complementary power generation based on internet of things

When traditional system is used to monitor wind-solar complementary power generation, there are problems such as large errors in temperature and wind speed acquired and high power consumption of nodes when the sensor transmits signals. Therefore, a security monitoring system for wind-solar complementary power generation based on internet of things (IoT) is designed. The system hardware is composed of I/O control panel, sensor, GPRS and data processing board. The system software mainly acquires data and processes the acquisition interrupt program. On this basis, the security monitoring of wind-solar complementary power generation is finally realised. The analysis of simulation experiments shows that compared with the traditional system, the data acquisition error of the proposed system is small, which is in good agreement with the actual value. Moreover, the power consumption of nodes is only 15.8 mw when the sensor transmits the signal, indicating that the system has strong reliability and practical application value.

Research on capacity optimization of micro-grid hybrid energy storage system based on simulated annealing artificial fish swarm algorith with memory function

The intermittence and uncertainty of wind power and photovoltaic power have hindered the large-scale development of both. Therefore, it is very necessary to properly configure energy storage devices in the wind-solar complementary power grid. For the hybrid energy storage system composed of storage battery and supercapacitor, the optimization model of hybrid energy storage capacity is established with the minimum comprehensive cost as the objective function and the energy saving and charging state as the constraints. A simulated annealing artificial fish school algorithm with memory function is proposed to solve the model. The results show that the hybrid energy storage system can greatly save costs and improve system economy.

Study of wind-solar complementary power system in zhongshan station of antarctic

Due to the environmental and transportation problems caused by conventional diesel power supply of the Antarctic Zhongshan Station,the wind-solar complementary power generation technology can not only guarantee the power supply demand but also protected the environment of the polar regions.Combined with the meteorological data of the Antarctic Zhongshan station and the data of the load electricity consumption,the system energy matching calculation is carried out,which shows that the wind-solar complementary power generation system can meet the load demand of the Antarctic Zhongshan station.Aiming at the extreme polar day-night phenomena and the perennial low-temperature environment,the energy management scheme in Antarctic Zhongshan station are proposed and a Maximum Power Point Tracking control strategy simulation experiment is carried out,the simulation results verify the feasibility of the control strategy.

Wind-solar Complementary Controller Design of Round frame Wind generators

A new-type wind-solar complementary controller applied to round frame wind generators was designed and realized. This wind generator could realize real-time adjustment of paddle angle according to wind power so as to reach high safety and sustainable power generation effect even under a hurricane. The controller was integrated with a stepping motor driver. Integral separation PID control algorithm was used to drive stepping motor and adjust paddle angle so as to realize closed-loop control of generator velocity. Three-phase charging method was used to realize three-phase charging of storage battery so as to effectively lengthen its service life. MPPT algorithm was used to realize wind-solar complementary maximum power point tracking, thus improving the controller efficiency. STM32F103RBT6 chip-based wind-solar complementary controller was designed to complete controller hardware design and software programming. The system prototype was fabricated and experimented, and the experiment indicated that this controller could realize generator velocity control and battery charging-discharging functions with high efficiency and steady and reliable operation.

Optimal Site Selection of Wind-Solar Complementary Power Generation Project for a Large-Scale Plug-In Charging Station

The wind-solar hybrid power generation project combined with electric vehicle charging stations can effectively reduce the impact on the power system caused by the random charging of electric cars, contribute to the in-situ wind-solar complementary system and reduce the harm arising from its output volatility. In this paper, the site selection index system of a landscape complementary power generation project is established by using the statistical methods and statistical analysis in the literature. Subsequently, using the Analytic Network Process to calculate the index weight, a cloud model was used in combination with preference ranking organization method for enrichment evaluations to transform and sort uncertain language information. Finally, using the results of the decision-making for the location of the Shanghai wind-solar complementary project and by carrying out contrast analysis and sensitivity analysis, the superiority and stability of the decision model constructed in this study was demonstrated.

Development of Wind-Solar-Diesel-Battery Integrated Seawater Desalination Device

The development to seawater desalination technology of new energy is the valid way of solving the energy shortage and environmental pollution in coastal and islands areas. It is introduced in this paper with the components, design methods and operation analysis to the pluripotent coupling reverse osmosis (RO) seawater desalination devices focusing on the wind-solar complementary power generation. The operation results are shown that, the power generation system in the combination of wind, solar energy, diesel generator and battery could provide stable electric energy to the seawater desalination device, the water quality generated is superior to the standard of drinking water, which could guarantee the water and electric power in remote island area. The container is used in such devices as the carrier to be moved rapidly with supplying water in emergence. The significant practical significance is realized to the water supply and demand on islands, offshore platform and ships and other special areas.

A Cyber-Physical System (CPS) Based Hybrid Micro-Grid Model with Wind-Solar Complementary Power

Micro-grid, which coordinates distributed energy resources in a decentralized way, is a promising approach to allow distributed energy resources to provide full benefits while reducing the control burden on the grid. By exploiting the concept of cyber-physical system (CPS), prediction can be easily incorporated into micro-grid, which helps the micro-grid work more effectively and safely. In such a case, in this paper, based on CPS, we propose a novel micro-grid model, within the framework of which, a more explicit wind-solar complementary power system is presented. Moreover, we show how the closed-loop control is implemented in the proposed model which is of benefit to the design of micro-grid.

Design of Wind-solar Complementary Power System Based on Progressive Fuzzy Control

In order to make a wind-solar complementary power system be a self-intervention controller, a new fuzzy control approach to hybrid power generation in wind and solar co-generation system is developed in this paper. Firstly, a new kind of structure of wind-solar complementary power system is designed. The method of double-fed brushless wind turbine sets is adopted, based on the principle of nonlinear control theory, according to the external excitation caused by the nonlinear changes of wind forces and wind speeds, for the purpose of capturing the wind power in the greatest degree. Meanwhile, the idea of extensional adaptive control on solar cells is adopted, also in order to transform the renewable energy to electrical power to the most degree. Secondly, according to the analysis on the characteristics of the multi-input and multi-output of the distributed wind-solar complementary power system, a progressive fuzzy control algorithm based on fuzzy control method and adaptive control theory is put forward to control the loading and unloading process congruously among the wind turbines, the solar cells and the grid. Finally, the simulation study is carried out. It is shown that the new kind of wind-solar complementary power system can achieve the balance quite well between the supply and the demand of the electrical energy automatically according to the load of system, under the premise of improving the utilization rate of renewable resources as much as possible.