Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Electromechanical Transient Modeling Analysis of Large-Scale New Energy Grid Connection

The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous machine.It also has the same inertia,damping,frequency,voltage regulation,and other external performance as the generator.It is the key technology to realize new energy grid connections’stable and reliable operation.This project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor.A new energy storage method is proposed.The mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power,state of charge,operation efficiency,dead zone,and inverter constraint.The rapid conversion of energy storage devices absorbs the excess instantaneous kinetic energy caused by interference.The branch transient of the critical cut set in the system can be confined to a limited area.Thus,the virtual synchronizer’s kinetic and potential energy can be efficiently converted into an instantaneous state.The simulation of power system analysis software package(PSASP)verifies the correctness of the theory and algorithm in this paper.This paper provides a theoretical basis for improving the transient stability of new energy-connected power grids.

Application of Power Electronics Converters in Renewable Energy

Against the backdrop of global energy shortages and increasingly severe environmental pollution,renewable energy is gradually becoming a significant direction for future energy development.Power electronics converters,as the core technology for energy conversion and control,play a crucial role in enhancing the efficiency and stability of renewable energy systems.This paper explores the basic principles and functions of power electronics converters and their specific applications in photovoltaic power generation,wind power generation,and energy storage systems.Additionally,it analyzes the current innovations in high-efficiency energy conversion,multilevel conversion technology,and the application of new materials and devices.By studying these technologies,the aim is to promote the widespread application of power electronics converters in renewable energy systems and provide theoretical and technical support for achieving sustainable energy development.

Multi-objective optimization scheduling for new energy power system considering energy storage participation

For the low utilization rate of photovoltaic power generation,taking a new energy power system constisting of concentrating solar power(CSP),photovoltaic power(PP)and battery energy storage system as an example,a multi-objective optimization scheduling strategy considering energy storage participation is proposed.Firstly,the new energy power system model is established,and the PP scenario generation and reduction frame based on the autoregressive moving average model and Kantorovich-distance is proposed.Then,based on the optimization goal of the system operation cost minimization and the PP output power consumption maximization,the multi-objective optimization scheduling model is established.Finally,the simulation results show that introducing energy storage into the system can effectively reduce the system operation cost and improve the utilization efficiency of PP.

An Overview on Advanced Grid-connected Inverters Used for Decentralized Renewable Energy Resources

并网逆变器是分散式可再生能源接入配电网的重要接口,随着分布式可再生能源渗透率的不断提高,并网逆变器在传统配电网中的地位越发突出。为了高效完成可再生能源分散式并网,并有效降低并网逆变器对电网的冲击,一些在装置上、结构上和功能上更加先进的并网逆变器成为了迫切的需求。针对现有的一些先进并网逆变器进行比较、分析和研究,从装置级、功能级和控制级的角度对现有先进并网逆变器进行综述。给出一些在结构上能更加灵活地将可再生能源分散接入配电网的硬件电路。研究一些适用于可再生能源分散接入的,使并网逆变器能虚拟同步发电机完成自治运行、电能质量治理、系统阻抗检测、网络阻抗控制等辅助控制功能。同时还对并网逆变器的并网同步算法和电流跟踪控制策略进行了探讨。最后,提出一个适合于可再生能源分散并网的先进并网逆变器框架。

Research on New Compressed Air Energy Storage Technology

In recent years, wind power generation and photovoltaic power generation have been developing rapidly, and the installed capacity of the new resources generation has been keeping a fast growth every year. But with the incorporation into the grid, the new resources generation that has the properties such as randomness and volatility causes certain risks to the power grid, which results in the falling of the incorporation proportion instead of rising. This paper describes the current status and development problems of the new energy in China, and gives a brief introduction of characteristics of various energy storage technologies. This paper focuses on the analysis of the compressed air energy storage technology in recent years and new developments and the latest technology at home and abroad, additionally, the paper introduces a new concept of the compressed air energy storage system.

Review of Black Start on New Power System Based on Energy Storage Technology

With the continuous development of new energy generation technology and the increasingly complex power grid environment,the traditional black start scheme cannot meet the requirements of today’s power grid in order to ensure the stable operation of the power system can be restored quickly in the face of large power outages,so a more complete black start scheme needs to be developed to cope with the new power system.With the development of energy storage technology,the limitations of the traditional black-start scheme can be solved by new energy farms with energy storage configuration.Therefore,this paper investigates the problems faced by black-start,the key technologies of energy storage assisted new energy black-start,and introduces the research related to new energy black-start technology to provide reference for future research and application of new energy black-start.

An assessment of global ocean wave energy resources over the last 45 a

Against the background of the current world facing an energy crisis,and human beings puzzled by the problems of environment and resources,developing clean energy sources becomes the inevitable choice to deal with a climate change and an energy shortage.A global ocean wave energy resource was reanalyzed by using ERA-40 wave reanalysis data 1957–2002 from European Centre for Medium-Range Weather Forecasts（ECMWF）.An effective significant wave height is defined in the development of wave energy resources（short as effective SWH）,and the total potential of wave energy is exploratively calculated.Synthetically considering a wave energy density,a wave energy level probability,the frequency of the effective SWH,the stability and long-term trend of wave energy density,a swell index and a wave energy storage,global ocean wave energy resources were reanalyzed and regionalized,providing reference to the development of wave energy resources such as wave power plant location,seawater desalination,heating,pumping.

Optimal configuration of 5G base station energy storage considering sleep mechanism

The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries.To maximize overall benefits for the investors and operators of base station energy storage,we proposed a bi-level optimization model for the operation of the energy storage,and the planning of 5G base stations considering the sleep mechanism.A multi-base station cooperative system composed of 5G acer stations was considered as the research object,and the outer goal was to maximize the net profit over the complete life cycle of the energy storage.Furthermore,the power and capacity of the energy storage configuration were optimized.The inner goal included the sleep mechanism of the base station,and the optimization of the energy storage charging and discharging strategy,for minimizing the daily electricity expenditure of the 5G base station system.Additionally,genetic algorithm and mixed integer programming were used to solve the bi-level optimization model,analyze the numerical example test comparison of the three types of batteries and the net income of the configuration,and finally verify the validity of the model.Furthermore,the sleep mechanism,the charging and discharging strategy for energy consumption,and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration.

Research on energy storage capacity configuration for PV power plants using uncertainty analysis and its applications

Compensating for photovoltaic(PV)power forecast errors is an important function of energy storage systems.As PV power outputs have strong random fluctuations and uncertainty,it is difficult to satisfy the grid-connection requirements using fixed energy storage capacity configuration methods.In this paper,a method of configuring energy storage capacity is proposed based on the uncertainty of PV power generation.A k-means clustering algorithm is used to classify weather types based on differences in solar irradiance.The power forecast errors in different weather types are analyzed,and an energy storage system is used to compensate for the errors.The kernel density estimation is used to fit the distributions of the daily maximum power and maximum capacity requirements of the energy storage system;the power and capacity of the energy storage unit are calculated at different confidence levels.The optimized energy storage configuration of a PV plant is presented according to the calculated degrees of power and capacity satisfaction.The proposed method was validated using actual operating data from a PV power station.The results indicated that the required energy storage can be significantly reduced while compensating for power forecast errors.

Optimal configuration strategy of energy storage system in high photovoltaic penetration micro-grid based on voltage sensitivity analysis

Energy storage is an effective measure to deal with internal power fluctuation of micro-grid and ensure stable operation, especially in the micro-grid with high photovoltaic(PV) penetration. Its capacity configuration is related to the steady, safety and economy of micro-grid.In order to improve the absorptive capacity of micro-grid on maximizing the use of distributed PV power in micro-grid, and improve the power quality, an optimal energy storage configuration strategy is proposed, which takes many factors into account, such as the topology of micro-grid, the change of irradiance, the load fluctuation and the cable. The strategy can optimize the energy storage allocation model to minimize the storage power capacity and optimize the node configuration.The key electrical nodes are identified by using the sensitivity coefficient of the voltage, and then the model is optimized to simplify calculation. Finally, an example of the European low-voltage micro-grid and a micro-grid system in the laboratory is used to verify the effectiveness of the proposed method.The results show that the proposed method can optimize the allocation of capacity and the node of the energy storage system.

Design of Low Carbon and Energy-saving New Rural Residential Buildings in Western Parts of Heilongjiang Province

It is researched that rural residential buildings in Heilongjieng consume high energy and the living environment is poor. The research aimed at designing low-carbon and energy-saving buildings in order to reduce energy consumption by applying energy storage. Besides, the research used composite solar panel, waste- based inorganic foam materials, and polystyrene board as construction materials and integrated energy collection, living environment and farming by energy storage system. It is notable that the research would reduce pollution on environment caused by residential buildings, which coincides with national economy development and en- ergy strategy, promoting construction material industry development, with high social and economic benefits.

Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

To reduce the comprehensive costs of the construction and operation of microgrids and to minimize the power fluctuations caused by randomness and intermittency in distributed generation,a double-layer optimizing configuration method of hybrid energy storage microgrid based on improved grey wolf optimization(IGWO)is proposed.Firstly,building a microgrid system containing a wind-solar power station and electric-hydrogen coupling hybrid energy storage system.Secondly,the minimum comprehensive cost of the construction and operation of the microgrid is taken as the outer objective function,and the minimum peak-to-valley of the microgrid’s daily output is taken as the inner objective function.By iterating through the outer and inner layers,the system improves operational stability while achieving economic configuration.Then,using the energy-self-smoothness of the microgrid as the evaluation index,a double-layer optimizing configuration method of the microgrid is constructed.Finally,to improve the disadvantages of grey wolf optimization(GWO),such as slow convergence in the later period and easy falling into local optima,by introducing the convergence factor nonlinear adjustment strategy and Cauchy mutation operator,an IGWO with excellent global performance is proposed.After testing with the typical test functions,the superiority of IGWO is verified.Next,using IGWO to solve the double-layer model.The case analysis shows that compared to GWO and particle swarm optimization(PSO),the IGWO reduced the comprehensive cost by 15.6%and 18.8%,respectively.Therefore,the proposed double-layer optimizationmethod of capacity configuration ofmicrogrid with wind-solar-hybrid energy storage based on IGWO could effectively improve the independence and stability of the microgrid and significantly reduce the comprehensive cost.

Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.

Smart Inverter Functionality Testing for Battery Energy Storage Systems

Variable distributed energy resources (DERs) such as photovoltaic (PV) systems and wind power systems require additional power resources to control the balance between supply and demand. Battery energy storage systems (BESSs) are one such possible resource for providing grid stability. It has been proposed that decentralized BESSs could help support microgrids (MGs) with intelligent control when advanced functionalities are implemented with variable DERs. One key challenge is developing and testing smart inverter controls for DERs. This paper presents a standardized method to test the interoperability and functionality of BESSs. First, a survey of grid-support standards prevalent in several countries was conducted. Then, the following four interoperability functions defined in IEC TR 61850-90-7 were tested: the specified active power from storage test (INV4), the var-priority Volt/VAR test (VV) and the specified power factor test (INV3) and frequency-watt control (FW). This study then out-lines the remaining technical issues related to basic BESS smart inverter test protocols.

Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based onMulti-Scale and Multi Feature Convolution Neural Network

There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.

Energy Storage and Multi-Source System for Reduction Energy Costs in the Consumer-Side

The objective of this work is to reduce energy costs for a consumer with multiple available energy resources and with an energy storage system. To achieve this, it is developed a methodology with a multi-criterion analysis that considers the demand side, the real-time prices, and the availability of the energy resources. In other words, the developed methodology manages the multi-source system, allowing savings for a consumer. In addition to the presentation of the methodology, it is made an application in a case study. It is considered and modeled a real consumer that has three different energy resources, including energy storage by battery. The situation comprehends solar generation, diesel generator and the electrical power grid. There are simulations and the results comprehend the savings for this consumer, considering the methodology application. The main result is a reduction in energy costs by 33.3%, considering the situation without this methodology. For the purpose of indicating the use of the storage system, it is presented the battery’s state of charge along the simulation. Also, there is a verification of the methodology’s robustness, through another simulation, using theoretical data for the consumer. In this case, the consumer has energy storage system, solar generation, biogas generator and the electrical power grid. In this situation, there is a reduction in energy costs by 30.2%, considering the situation without this methodology. In conclusion, the results show that the developed methodology is effective. In the two case studies presented there are significant savings for the consumer.

Research of Thermal Energy Storage Technology in the Solar Thermodynamic Power

Recently, although renewable energy has a great development, primary source is still thermal power generation, which uses fossil fuel as the energy source. Supply and demand of fossil fuel are essential for social and economy development. However, development pattern that excessively relies on the natural source is impossible to provide a sustainable development way for us. As a result, we should combine renewable energy with new energy technology as the aim of economy. It means that it is urgent to exploit new energy. Meanwhile, the ratio of energy waste cannot be ignored. How to decrease energy waste is also significant. Construction sector costs a lot of energy, which is mainly used for heating and refrigeration. In the new energy generation technology, thermal energy can be transformed to electricity with combination of BIPV and thermal energy storage technology. Photovoltaic generation has a great progress in the building construction. As a result, the thermal energy storage technology becomes the key link in the production chain. In this paper, feasibility of applying phase-change material (PCM) in the thermal energy storage will be analyzed. And analysis results are provided with a relative mathematical model.

Research on Landscape Ecology Mode of New Resources-based Cities—A Case Study of Yulin City of Shaanxi Province in China

Based on the overall understanding of new cities developing based on resources,by taking Yulin City of Shaanxi Province for example and combining with relevant statistical data,main problems existing in resources development have been pointed out,covering simple resources industrial structure and serious wastes in resources development;insufficient intensive processing of products and low level of resources integrated utilization;and deteriorative regional eco-environment.On this basis,a new mode of landscape ecology of resource-based cities have been proposed,emphasizing constructing new green energy industrial development mode from the perspective of microscopic view;ecological industrial park of circular economy from the perspective of mesoscopic view;and the overall ecological recovery mode of the mining area from the perspective of macroscopic view.It hopes to give a vital inspiration to the sustainable development of new resources-based cities.

Incremental cost analysis model of distribution network based on economic dispatch of distributed new-energy storage system

With the implementation of China’s carbon-peaking and carbon-neutrality strategy,new energy will achieve leapfrog growth.Due to the good economics of distributed new-energy generation,it can not only save users’own investment,but also help to achieve local consumption of new energy.However,it will also bring about a series of incremental costs to the power grid.This paper first enumerates the concept,development status and scheduling mode of a distributed new-energy storage system.Based on the above,it establishes a new-energy power generation model and an energy storage system charging and discharging model,and proposes a global optimization scheduling model for a distributed new-energy storage system,considering the time-of-use electricity price and taking the lowest total operating cost of the distributed new-energy power generation system as the objective function.Finally,it proposes a distribution network incremental cost analysis model based on the penetration of distributed new energy.The calculation results show that the incremental cost of grid-connected distributed new energy is 1.0849,1.2585 and 1.3473 yuan/kWh,respectively,which indicates that the global dispatching model can optimize the power consumption structure of a distributed power generation system,and has the function of peak shaving and valley filling,but the incremental cost of the distribution network will also increase.