Enhanced Electric Power Adaptability Using Hybrid Pumped-Hydro Technology with Wind and Photovoltaic Integration

The integration of solar and wind energy into the electrical grid has received global research attention due to their unpredictable characteristics.Because wind energy varies across all timescales of utility activity,renewable energy generation should be supplemented and enhanced,from real-time,minute-to-minute variations to annual alterations influencing long-termstrategy.Wind energy generation does not only fluctuate but is also challenging to accurately forecast the timeframes of significance to electricity decision makers;day-ahead and long-term making plans of framework sufficiency such as meeting the network peak load annually.A utility that integrates wind and solar energy into its electricity mix would understand how to adapt to uncertainty and variability in operations while sustaining grid stability.Due to hydropower’s adaptability,a system using hydropower as one of its generating resources could be precisely adapted to absorb the variability of wind and solar energy.The objective of this research study is to create a hybrid system comprising hydro-wind and solar(Hybrid-HWS)integration for power balancing in an isolated electrical network in Klipkop village,Pretoria region,South Africa.The desirability of designing and building goaf storage tank in regard to capability,the fullness of line throughoutwater pumping,dispensing,storage tank spillage,and pressure difference throughout liquid flow within the storage tanks were preliminary assessed using geotechnical and weather forecasting data from a distinctive area of Klipkop town in Pretoria,South Africa.Different facility hours premised on daylight accessibility are scheduled to balance maximum load at early and late hours.However,in the scenario of electrical power,time shift requiring storage for extended periods of time,such as in terms of hours,Hybrid-HWS has been found to have a crucial role.The results of simulations showed a coordinated process design for Hybrid-HWS Energy Storage(ES)to determine everyday strategic planning in reducing the variability of the system resulting from wind-solar-pumped hydro ES output inadequacies and satisfy daily load demands.It could be recommended that by considering the adaptability characteristics,extremely rapidly,ramping,peaking support and maximum stabilizing aid of the system could be archived with pump-hydro into the energy mix which can provide specific guidelines for energy policymakers.

Hybrid model based on K-means++ algorithm, optimal similar day approach, and long short-term memory neural network for short-term photovoltaic power prediction

Photovoltaic(PV) power generation is characterized by randomness and intermittency due to weather changes.Consequently, large-scale PV power connections to the grid can threaten the stable operation of the power system. An effective method to resolve this problem is to accurately predict PV power. In this study, an innovative short-term hybrid prediction model(i.e., HKSL) of PV power is established. The model combines K-means++, optimal similar day approach,and long short-term memory(LSTM) network. Historical power data and meteorological factors are utilized. This model searches for the best similar day based on the results of classifying weather types. Then, the data of similar day are inputted into the LSTM network to predict PV power. The validity of the hybrid model is verified based on the datasets from a PV power station in Shandong Province, China. Four evaluation indices, mean absolute error, root mean square error(RMSE),normalized RMSE, and mean absolute deviation, are employed to assess the performance of the HKSL model. The RMSE of the proposed model compared with those of Elman, LSTM, HSE(hybrid model combining similar day approach and Elman), HSL(hybrid model combining similar day approach and LSTM), and HKSE(hybrid model combining K-means++,similar day approach, and LSTM) decreases by 66.73%, 70.22%, 65.59%, 70.51%, and 18.40%, respectively. This proves the reliability and excellent performance of the proposed hybrid model in predicting power.

Economic feasibility of large-scale hydro–solar hybrid power including long distance transmission

Solar PV is expected to become the most cost-competitive renewable energy owing to the rapidly decreasing cost of the system. On the other hand, hydropower is a high-quality and reliable regulating power source that can be bundled with solar PV to improve the economic feasibility of long-distance transmitted power. In this paper, a quantification model is established taking into account the regulating capacity of the reservoir, the characteristics of solar generation, and cost of hydro and solar PV with long-distance transmission based on the installed capacity ratio of hydro–solar hybrid power. Results indicate that for hydropower stations with high regulating capacity and generation factor of approximately 0.5, a hydro–solar installed capacity ratio of 1:1 will yield overall optimal economic performance, whereas for hydropower stations with daily regulating capacity reservoir and capacity factor of approximately 0.65, the optimal hydro–solar installed capacity ratio is approximately 1:0.3. In addition, the accuracy of the approach used in this study is verified through operation simulation of a hydro–solar hybrid system including ultra high-voltage direct current(UHVDC) transmission using two case studies in Africa.

Research and practice of designing hydro/ photovoltaic hybrid power system in microgrid

Small-hydro power station is often used in remote areas beside a river,but it doesn't match electricity demand so well,especially in dry seasons. A photovoltaic (PV) system with battery is a suitable option to complement the electricity gap. In this paper,a new structure of megawatt-class PV system integrating battery at DC-bus (DC: direct current) is proposed to be used in hydro/PV hybrid power system,and 4 main designing considerations and several key equipments are discussed. In 2011,a 2 MWp PV station with the proposed structure was built up in Yushu,China. From stability analysis,the station shows a strong stability under load cut-in/off and solar irradiance's fluctuation.

Feasibility Study of a Hydro PV Hybrid System Operating at a Dam for Water Supply in Southern Brazil

Dams for water supply usually represent an untapped hydroelectric potential. It is a small energetic potential, in most situations, usually requiring a particular solution to be viable. The use of pumps as power turbines often represents an alternative that enables the power generation in hydraulic structures already in operation, as is the case of dams in water supply systems. This potential can be exploited in conjunction with the implementation of PV modules on the water surface, installed on floating structures, both operating in a hydro PV hybrid system. The floating structure can also contribute to reducing the evaporation of water and providing a small increase in hydroelectric power available. This paper presents a pre-feasibility study for implementation of a hydroelectric power plant and PV modules on floating structures in the reservoir formed by the dam of Val de Serra, in southern Brazil. The dam is operated to provide drinking water to about 60% of the population of the city of Santa Maria, in the state of Rio Grande do Sul, in southern Brazil. The pre-feasibility study conducted with Homer software, version Legacy, indicated that the hydroelectric plant with a capacity of 227 kW can operate together with 60 kW of PV modules. This combination will result (in one of the configurations considered) in an initial cost of USD$ 1715.83 per kW installed and a cost of energy of USD$ 0.059/kWh.

Maximum Power Point Tracking Based on Improved Kepler Optimization Algorithm and Optimized Perturb&Observe under Partial Shading Conditions

Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall into local optima and fail to find the global optimum.To address this issue,a composite MPPT algorithm is proposed.It combines the improved kepler optimization algorithm(IKOA)with the optimized variable-step perturb and observe(OIP&O).The update probabilities,planetary velocity and position step coefficients of IKOA are nonlinearly and adaptively optimized.This adaptation meets the varying needs of the initial and later stages of the iterative process and accelerates convergence.During stochastic exploration,the refined position update formulas enhance diversity and global search capability.The improvements in the algorithmreduces the likelihood of falling into local optima.In the later stages,the OIP&O algorithm decreases oscillation and increases accuracy.compared with cuckoo search(CS)and gray wolf optimization(GWO),simulation tests of the PV hybrid inverter demonstrate that the proposed IKOA-OIP&O algorithm achieves faster convergence and greater stability under static,local and dynamic shading conditions.These results can confirm the feasibility and effectiveness of the proposed PV MPPT algorithm for PV hybrid systems.

Influence of Time Complementarity on Energy Storage through Batteries in Hydro PV Hybrid Energy System

The notion of energetic complementarity can be a tool for energy resource managers to prioritize energy generation projects based on renewable resources in both interconnected and independent systems. As a tool in decision-making, it is important to know better the influence of energetic complementarity on the performance of hybrid systems especially with regard to energy shortages but also in relation to other parameters. In recent years, hydro PV hybrid systems have become a growing target of researchers and designers for the idea of installing photovoltaic modules on the water surface of reservoirs. Energetic complementarity has three components: time-complementarity, energy-amplitude and amplitude-complementarity. This paper is dedicated to the study of the influence of time-complementarity on the storage of energy through batteries in hydro PV hybrid systems. The method applied is in the literature and suggests the simulation of the system under study with the idealization of energy availabilities, to remove the effects of climatic variations and the characteristic intermittency of renewable resources. Simulations were performed with the well-known software Homer. The results provided the variations of the states of charge of the batteries as a function of different time-complementarities, indicating as expected better performances associated to higher time-complementarities. The results indicated that the cost of energy for a hybrid system with 28 batteries was equal to US$ 0.502 per kWh and that this cost increased as the time complementarity between energy resources moved away from the situation corresponding to full complementarity. The simulations also showed that the maintenance of the zero failure condition supplying the demands of the consumer loads requires that the load be reduced to 52% if the complementarity is reduced from the full complementarity to zero complementarity, with the cost of energy going from US$ 0.502 per kWh to US$ 0.796 per kWh. The results also allow a better understanding of the influence of time complementarity on the performance of hybrid systems.

Design of Real Time Battery Management Unit for PV-Hybrid System by Application of Coulomb Counting Method

This paper presents a real-time battery management unit designed by applying the Coulomb counting method and intended for use in an integrated renewable energy system for PV-Hybrid power supply. Battery management is required to stabilize hybrid systems and extend battery lifetimes. The battery management unit is divided into three main stages. Firstly, analysis of the basic components of the battery type used in the system is considered. Secondly, the state of charge (SOC) estimation method and the deterioration factor of the battery are analyzed. Finally, the overall battery management system, including a computer-based measurement and control unit, is constructed. The control system displays real-time information through LabVIEW 8.5 by estimating the state of charge through various measurements. The system will issue alerts when malfunctions are detected, and the operator can analyze and react to the system in real time to stabilize the system and extend the battery lifetime.

Economic Analysis and Environmental Impacts of a Hybrid PV System in Arid Climate Considering Different Types of Solar Trackers

This paper presents a study aimed at evaluating and comparing the performance of six different tracking systems for photovoltaic (PV) with diesel-battery hybrid system in arid climate of Kingdom of Saudi Arabia (KSA). The study considered various technical and economic factors including system net present cost (NPC), levelized cost of energy (LCOE), and PV power generation using energy analysis and microgrid design software “HOMER”. It also presents an overview of the current electricity production and demand in the Kingdom. The weather data used in this study have been collected from the new solar atlas launched by King Abdullah City for Atomic and Renewable Energy (KACARE). The selected solar resource monitoring station for this study is located near to Riyadh city and has an annual average daily total irradiation of 6300 W/m2/day. The study shows that, for stand-alone PV system in the vicinity of Riyadh city, tracking system is economically better than fixed angle system. Among the considered tracking systems, VCA system is the most preferable as it has low NPC and LCOE values with a high return on investment (ROI) as well as low carbon dioxide (CO2) emissions due to a high renewable energy penetration.

Feasibility Study for Power Generation during Peak Hours with a Hybrid System in a Recycled Paper Mill

The differential pricing for peak hours encourages industrial consumers to look for independent power supplies for the period from 19 to 22 hours. This paper presents a study to identify the optimal solution for a recycled paper mill that also intends to work in that period. The factory is located in Rio Grande do Sul, in southern Brazil, and considers the use of a diesel gen set, a micro hydro power plant and possibly PV modules. Two micro hydro power plants were considered in the study, an old plant to be renewed and another to be fully implemented. The software Homer was used as a tool to determine the most feasible combination of components considered in the study. The sale of surplus power to the energy system appears as a key to viability of alternatives that are not based solely on diesel generators. The optimal solution consists of a combination of diesel generators and micro hydro power plant, in one case, and only on hydroelectric power plant in another, with a significant penetration of PV modules if its cost is reduced to 12% of the current price, selling an amount of energy equal to that which is bought. The annual water availability in one of the sites requires diesel supplement, while the other, more abundant, this supplement is not necessary.

基于EnKF的水光互补系统适应性调度规则敏感性分析

水光互补是解决电力能源供应问题、构建低碳能源体系、实现“双碳”目标的重要举措。采用集合卡尔曼滤波对线性调度函数的参数进行动态更新,构建了水光互补中长期适应性调度规则,并以龙羊峡水光互补电站为研究对象,在同化过程中引入预测误差、观测误差及集合规模3个不确定性参数,分析了不确定性参数取值对模型时变参数和运行结果的影响,并对参数的敏感性进行了定性分析。结果表明,预测误差、观测误差及集合规模对模型时变参数和运行结果没有显著影响,三者均不是敏感性参数。研究结果可为集合卡尔曼滤波参数不确定性分析及多能互补系统适应性调度研究提供参考。

基于指数分布优化器的混合光伏-温差系统最大功率点跟踪

为解决混合光伏-温差(photovoltaic thermoelectric generator,PV-TEG)系统的最大功率点跟踪(maximum power point tracking,MPPT)问题以提高能源转换效率和利用率,提出了一种基于指数分布优化器(exponential distribution optimizer,EDO)的混合PV-TEG系统MPPT技术。EDO通过模拟指数分布的随机变化来搜索潜在的解空间,由于随机性,算法可有效避免在局部遮蔽条件(partial shading condition,PSC)下陷入局部最优,并在搜索空间中广泛探索以找到最优解。算例研究包括启动测试、太阳辐照度阶跃变化、随机变化、香港地区四季实际算例4个部分,并与其他5种算法进行对比分析,以较为全面地验证所提EDO技术在混合系统MPPT应用中的可行性和有效性。仿真结果表明,采用EDO的混合PV-TEG系统在不同运行条件下均能稳定、高效地实现最优越的MPPT性能,尤其是在春季低辐照度的条件下,EDO产生的能量分别超过蜻蜓算法(dragonfly algorithm,DA)、增量电导法(incremental conductance method,INC)、扰动观测法(perturbation observation method,P&O)能量输出的68.85%、66.13%和59.69%。

计及混合储能寿命损耗的光伏功率平抑策略

针对光伏大规模并网产生的功率波动问题,提出了一种计及混合储能寿命损耗的光伏并网功率平抑策略。该策略根据光伏功率与并网功率波动允许范围的关系确定混合储能动作状态及功率指令,实现了光伏并网功率波动的平抑;然后建立了关于混合储能系统功率协调控制的多目标优化模型,并利用带精英策略的快速非支配排序遗传算法求解该模型;最后对平抑及功率协调控制进行了仿真验证。与传统平抑策略相比,所提策略在实现光伏并网功率波动平抑的基础上,有效降低了混合储能系统的寿命损耗与运行损耗。

交直流互联系统节点PV曲线的求取

针对交直流互联系统电压稳定性的计算问题,给出了交直流互联系统各节点PV曲线的求取方法。该算法采用基于统一迭代法的连续潮流法,在临界点附近采取缩小步长的策略,可以精确求出整个PV曲线并得到精确临界点。研究了负荷和发电机出力的不同变化方式及各种直流控制方式对PV曲线的影响等问题,并做了系统实例计算。计算结果表明,文中提出的算法能快速完整地得到交直流互联系统PV曲线。

不同风光水配比下多类型电源打捆直流外送系统的功率传输能力研究

风光水打捆经电网换相换流器高压直流输电(line commutated converter based high voltage direct current,LCC-HVDC)外送系统中,风光水配比不同会影响系统的功率传输能力。文章首先建立风光水打捆直流外送系统的稳态数学模型和状态空间模型,然后提出综合考虑稳态运行约束条件和小信号稳定性约束条件的系统功率传输能力计算方法及流程,掌握不同功率水平下系统稳定运行区域及边界的变化特征,最终得到不同水电出力下的直流外送系统功率传输范围、特定传输功率下所允许的水电出力最小值、风光配比与小信号稳定性的定量关系。通过该方法定量评估风光水配比不同时直流外送系统的功率传输能力,从而优化选取风光水配比。结果表明,水电出力较小时,系统传输功率上限受小信号稳定性制约,下限受电压偏移约束制约;水电出力较大时,系统传输功率上限受LCC-HVDC安全运行约束制约,下限受逆变侧电压偏移、系统潮流约束制约;在功率运行点不变时,风光配比平衡工况系统更加稳定。最后,通过PSCAD/EMTDC下的电磁暂态仿真,验证上述功率传输能力理论计算的正确性。

基于MPC的光-储协同调频优化策略

[目的]为了降低光伏发电给电网带来的频率扰动,并进一步提升调频效果,提出了一种基于MPC(Model Predictive Control)的光-储协同调频优化策略,分析了该策略的基本原理、控制流程、约束条件、目标函数并优化了权重系数。[方法]构建了一个基于MPC的光-储并网系统模型,并根据该模型推导出了非线性状态空间方程。为了验证该策略的调频效果,设置了4种不同的仿真环境:无储能、带电池储能、带混合储能以及文章提出的策略。[结果]仿真结果表明:与其他场景相比,所提出的策略在调频效果上是最优的,无储能的条件下调频效果是最差的,此外,采用混合储能的调频方法优于使用电池储能的方法。[结论]在MATLLAB/Simulink平台上验证了所提策略的有效性。在光伏发电系统中,对储能和光伏最大功率点跟踪进行优化控制,能使电网频率更加稳定,从而提高整个系统的稳定性。该研究成果可为光伏发电并网提供参考依据。

基站叠光系统故障诊断方法

叠光技术已在通信基站开展规模应用,但由于基站位置分布分散,光伏设备对维护人员专业技能要求较高,基站叠光系统定期巡检上站成本高、维护难度大。在调研基站叠光系统常见故障类型的基础上,开展基站实地故障模拟试验,建立基站叠光系统典型故障特征模型,提出同站址光伏组件之间发电数据横向比较、历史发电数据纵向比较的故障诊断方法。利用现网叠光基站发电数据进行算法验证,其中周期性固定物阴影遮挡诊断正确率达到88%。该方法可以有效定位基站叠光系统故障光伏组件和故障原因,降低定期上站巡检成本和维护人员技能要求,提高了运营维护效率,具有良好应用前景。

一种基于混合储能改善跟踪光伏发电出力特性方法的研究

光伏输出受天气影响具有较大波动性,若直接接入电网则会对电网的电能质量造成严重影响。为减轻光伏电站并网功率对电网的影响,提出了一种基于氢与电池混合储能改善跟踪光伏发电出力特性的方法。首先,利用高斯函数逼近光伏预测功率,形成光伏次日出力计划,并根据次日凌晨电池SOC大小和氢储能调节灵活性对出力计划进行修正。考虑氢储能和电池储能运行状态,设计了包含有主调度和协调调度的实时调度方案。最后,通过算例验证了所提方法的有效性。

基于QMD-HBi GRU的短期光伏功率预测方法

为了解决光伏功率数据固有的强不确定性导致单一预测模型预测精度不高的问题,提出一种基于二次模态分解和混合双向门控循环单元模型(hybrid bi-directional gated recurrent unit, HBiGRU)的短期光伏功率预测方法。首先,为应对光伏功率数据的不确定性,基于自适应噪声完备集合经验模态分解、样本熵和变分模态分解对光伏功率数据进行处理,得到一系列较为平稳的本征模函数分量;其次,构建HBi GRU模型以充分挖掘各分量与光伏功率影响因素之间的特征关系,得到各分量预测结果;最后,将各分量预测结果叠加得到短期光伏功率预测结果。以澳大利亚某地光伏电站数据进行测试,仿真结果表明:所提集成预测模型能够有效提高短期光伏功率预测精度,与其他预测模型相比,其归一化平均绝对误差和均方根误差分别降低了3.21%和5.04%,决定系数提高了22.7%。