郑州市风光互补发电经济技术分析

风光互补发电系统是城市利用可再生能源最成熟、最广泛的一种方式。虽然郑州市是太阳能和风能资源都不丰富地区,但根据郑州市风能和太阳能资源特点,通过对风能和光伏发电系统进行经济技术分析后发现,风光互补发电在郑州市仍是有利用价值的。     

风光互补系统多阶段充电控制策略研究

随着风光互补发电技术的发展,储能单元已成为风光互补发电系统的重要组成部分,储能单元的优劣将直接影响到系统的整体性能.针对风光互补发电系统自身的特点,提出了基于风光互补发电系统的铅酸蓄电池多阶段充电控制策略.通过对不同阶段充电控制策略的控制调节,可以使蓄电池在环境发生变化时仍然可以得到合理有效的充电效果;通过合理的转换和控制电路使风能与太阳能资源得到最大限度的存储与利用;通过系统仿真与实验验证了蓄电池多阶段充电控制策略的合理性与可实施性.     

北疆地区风光互补发电最佳配比方案的研究

利用中间插值逼近算法分析风能和太阳能发电量的最优匹配方案以及相应的碳节约排放量。结果表明,新疆在未来的发展趋势下,风光互补发电中风能仍然占据了大份额。     

太阳能烟囱与垂直轴风机耦合发电可行性分析

通过分析太阳能烟囱热气流发电和垂直轴风力机发电的技术及特点,提出了太阳能热气流烟囱与垂直轴风力机耦合发电的方法。对风力机—太阳能热气流烟囱互补发电系统的可行性进行了分析。互补发电的功率输出持续、稳定,具有大规模并网的良好条件,是实现太阳能与风能综合利用的有效途径。     

华东沿海海洋温差发电系统的优化设计

海洋温差能是一种可再生的绿色能源,储藏量大,资源稳定。海洋温差发电是利用深层、表层海水的温度差,以高温海水为热源,使液态工质气化推动发电机发电,以低温海水为冷源,使气态工质液化的不断循环的过程。基于能源的可持续发展考虑,可以利用风能、太阳能等可再生能源来优化设计海洋温差发电系统。华东沿海海域有着丰富的太阳能和风能资源,利用太阳能可以提高表层海水与深层海水的温差,利用风力转化装置可以提高和调整汽轮机的转速,保证发电系统持续稳定的发电。利用太阳能、风能对海洋温差发电系统进行优化设计,不仅避免和解决了当前海洋温差发电技术上的一些难点,还扩大了应用温差能资源的海域范围。     

季节对风光互补发电特性的影响

通过对风光互补发电系统输出功率的详细分析,结合唐山市风能、太阳能资源的时间、空间分布情况,从风光发电特性和电量的角度,验证风能、太阳能在时间上的互补特性。根据不同气象条件下,实际运行中风光互补系统发电数据的统计分析计算,研究气候因素对风光互补发电系统的影响。     

离网型风光互补发电系统匹配程序设计

以使用风力发电为主、光伏发电作为补充的原则进行风光互补发电系统优化设计的研究。通过合理选择风力机型号和光伏板安装倾角,充分利用了风能和太阳能的互补性,使用Matlab开发设计出风光互补发电系统匹配的优化程序。根据该优化方法设计的计算程序能更准确地设计出风光互补发电系统的匹配容量,中文化的参数操作界面在使用时更加方便直观,在实际工程使用时更加简单、实用。     

风-光互补发电系统

在目前利用的诸多新能源中,太阳能与风能处于特别引人注目的地位。在我国很多地区（约占全国面积的２/３）,太阳能与风能具有一定的互补特性,即两者在上下两个半年中在变化趋势上呈现完全相反的特性,这种特性为太阳能与风能的互补（联合）发电提供了可能,与风力发电机或太阳光伏电池单独发电系统相比,互补发电系统的供电质量有较大提高,而系统的重复投资则有所下降。一风光互补发电系统风能与太阳能的随机性强,随季节、时间、天气等条件的变化差异很大。为保证供电质量,在单独发电或互补（联合）发电系统中都必须配备储能环节。构成储能环节…     

可再生能源联合发电技术

近年来,随着国家倡导低碳经济,以风电、水电、太阳能、生物质能为代表的新能源得到了快速的发展。风能、水能、太阳能、生物质能等多种可再生能源联合发电是一种有效的可再生能源利用方式。简述了风能、水能,太阳能和生物质能的发电原理,并探讨了目前国内关于多种能源联合互补发电系统的设计研究成果。     

风光互补技术及应用新进展

简要回顾国内外风电、光伏技术与应用发展态势,结合风光互补系统应用,分析、介绍了风光互补LED路灯照明系统、智能控制器设计、分布式供电电源、风光互补水泵系统．并着重分析生物质能、风能和太阳能互补分布式能源梯级系统原理,涉及的技术关键等。研究表明,风能、光伏发电应用需要实现低成本、规模化,风光互补技术应用前景广阔。     

Design and techno-economical optimization for stand-alone hybrid power systems with multi-objective evolutionary algorithms

The optimal design of the hybrid energy system can significantly improve the economical and technical performance of power supply. However, the problem is formidable because of the uncertain renewable energy supplies, the uncertain load demand, the nonlinear characteristics of some components, and the conflicting techno-economical objectives. In this work, the optimal design of the hybrid energy system has been formulated as a multi-objective optimization problem. We optimize the techno-economical performance of the hybrid energy system and analyse the trade-offs between the multi-objectives using multi-objective genetic algorithms. The proposed method is tested on the widely researched hybrid PV-wind power system design problem. The optimization seeks the compromise system configurations with reference to three incommensurable techno-economical criteria, and uses an hourly time-step simulation procedure to determine the design criteria with the weather resources and the load demand for one reference year. The well-known efficient multi-objective genetic algorithm, called NGAS-II (the fast elitist non-dominated sorting genetic algorithm), is applied on this problem. A hybrid PV-wind power system has been designed with this method and several methods in the literature. The numerical results demonstrate that the proposed method is superior to the other methods. It can handle the optimal design of the hybrid energy system effectively and facilitate the designer with a range of the design solutions and the trade-off information. For this particular application, the hybrid PV-wind power system using more solar panels achieves better technical performance while the one using more wind power is more economical. Copyright © 2006 John Wiley & Sons, Ltd.     

Simultaneous synthesis of H2, O2, and N2 via an innovatory energy system in Coronavirus pandemic time: Design,techno-economic assessment,and optimization approaches

In this work, an innovative integrated system that is incorporated from solid oxide electrolysis cells and an oxygen separator membrane is assessed and optimized from the techno-economic aspects to respond to oxygen, hydrogen, and nitrogen demands for hospitals and other health care applications. Besides, a parametric comparison is conducted to apprehend the weights of parameters changes on the performance of criteria. Relying on the assessments, from the hydrogen production of 1 kg/s, 23.19 kg/s of oxygen, and 50.22 kg/s of nitrogen are produced. The parametric study shows that by raising the working temperature of the electrolyzer, the cell voltage variation has descending trend and the power consumption of the system is decreased by 19%. Finally, the results of multi-criteria optimization on the Pareto front reveal that in the optimal case, the system payback period is attained at about 5.32 years and the exergy efficiency of 92.47%, which are improved 16.6% and 16.2% compared to the base case, sequentially. Consequently, this system is proposed to consider as a cost-effective and reliable option towards its vital and valuable productions, in the pandemic period and after's.     

南方电网风电功率预测系统应用扩展研究

相比北方大型风电大多建于较为平坦内陆区域,南方电网区域内很多风电场则建设在相对复杂的地形环境,其中较有代表性的是高山、丘陵和海岸风电场,给风电功率预测系统的运行提出较大挑战。风电功率预测系统应用扩展性研究目的是使预测系统能在复杂而多变的实际现场应用场景下保持一定精度水平,满足系统用户需求。研究了南方电网区域内典型风资源特性和风电出力特性,根据这些特性,围绕当前预测系统功能流程中的三个主要技术环节——多输入数据源、功率预测建模和预测结果展现,提出应用扩展性研究框架。该项工作可以用于在数值天气预报精度有限的条件下改善预测精度,并且指导预测系统各技术环节中子技术选项的灵活组合方案,提高预测系统在工程现场的应用价值。基于南方电网区域内某风电场历史数据,论证了所提方法的有效性。     

A heuristic approach for optimal sizing of ESS coupled with intermittent renewable sources systems

In this paper a techno-economic comparison of an energy storage system (ESS) sizing for three intermittent renewables, wind, wave and PV power, with regard to two electricity grid services is presented. The first service consists of output hourly smoothing, based on day-ahead power forecasts (S1). The second service supplies year-round guaranteed power (S2). This leads to an annual default time rate (DTR) for which the actual power supplied to the grid does not match the day-ahead power bid within a given tolerance. A heuristic optimization based on an Adaptive Storage Operation (ASO) scheduling is developed in this study. ASO enables the minimal 5%-DTR ESS capacity, power, energy and feed-in-tariffs to be inferred from the operating conditions, depending on tolerance. The simulations assess and compare the techno-economic viability and efficiency of every renewable sources coupled with ESS. PV power is more efficient with daylight hours restricted services and higher power levels can be guaranteed for S1. Wind and wave power are more suitable than PV for services dedicated to full-day power delivery, as in the case of S2. For hourly smoothing the forecast accuracy influence is studied and yields a high impact on techno-economic sizing.     

Electrical collector system options for large offshore wind farms

The work presented is part of the EC FP6 DOWNVIND project activities, which focus on the requirements and implications of very large offshore wind farms. A comparative analysis of various design options for the electrical collector system of large offshore wind farms is presented, and the advantages and disadvantages in terms of their steady-state performance and economics are discussed. The case under consideration is that of a proposed 1-GW wind farm located off the northeast coast of Scotland. The impact on power losses and voltage level changes on the collector system busbars are investigated under various operating conditions. Contingency conditions of losing one of the cables to the hub end are also explored for collector system designs with redundant cables. Finally, the authors introduce an alternative design, based on conceptual ringed arrangements, and its advantages are illustrated and discussed     

Using hydropower to complement wind energy: a hybrid system to provide firm power

This paper presents a theoretical study of how wind power can be complemented by hydropower. A conceptual framework is provided for a hybrid power station that produces constant power output without the intermittent fluctuations inherent when using wind power. Two hypothetical facilities are considered as case studies. One of them is a hydropower plant located on the “Presidente Benito Juarez” dam in Jalapa del Marques, Oaxaca, Mexico. The other hypothetical facility is a wind farm located near “La Venta”, an area in Juchitan, Oaxaca, Mexico. The wind–hydro-power system is a combined wind and hydro power plant in a region that is rich in both resources. The model shows that the hybrid plant could provide close to 20 MW of firm power to the electrical distribution system. On a techno-economic basis, we obtain the levelized production cost of the hybrid system. Taking into account two different discount rates of 7% and 10%, figures for levelized production cost are developed.     

Steady-state modelling of hybrid energy system for off grid electrification of cluster of villages

Electrification of villages from the main grid leads to large investments and losses, and this forms the basis of decentralized Hybrid Energy System. In order to evaluate the techno-economic performance of hybrid energy system for remote rural area electrification, a mixed integer linear mathematical programming model (time-series) has been developed to determine the optimal operation, optimal configuration including the assessment of the economic penetration levels of photovoltaic array area, and cost optimization for a hybrid energy generation system consisting of small/micro hydro based power generation, biogas based power generation, biomass (fuelwood) based power generation, photovoltaic array, a battery bank and a fossil fuel generator. An optimum control algorithm written in C++, based on combined dispatch strategy, allowing easy handling of the models and data of hybrid energy system components is presented. A special feature of the proposed model is that a cost constant (cost/unit) for each of the proposed resource is introduced in the cost objective function in such a way that resources with lesser unit cost share the greater of the total energy demand in an attempt to optimize the objective function.To demonstrate the use of model and algorithm, a case study for a rural remote area is also presented.     

An improved global wind resource estimate for integrated assessment models

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km² deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.     

基于多储能技术经济性比较的可再生能源发电系统多目标容量优化

研究基于蓄电池、熔盐储热、抽水蓄能及储氢技术经济性比较的可再生能源发电系统多目标容量优化。该容量优化模型以最小化平准化度电成本及失负荷率为目标,应用4种代表性多目标进化算法进行求解。提出基于超体积的多目标算法综合评价指标,此外考虑了储能运行特性及资源不确定性提高仿真计算的准确性。算法性能比较结果表明,非劣排序遗传算法的平均排序等级为1.6,其具有最优的综合性能;储能的定量技术经济性比较结果表明,不同可靠性条件下熔盐储热系统的经济性均为最优;不同负荷曲线及不同资源水平的敏感性分析验证了储能经济性比较结果的有效性。     

Simulation of a novel hybrid solar photovoltaic/wind system to maintain the cell surface temperature and to generate electricity

A hybrid solar photovoltaic/wind system is proposed and investigated theoretically. The hybrid system is based on attaching a converging inclined duct beneath the photovoltaic (PV) panels and directed upward after the end of the panels. A wind turbine is attached at the exit of the converging duct. The converging duct will capture wind currents that at its inlet and enhances these current by buoyancy effect created by the rejected heat from the panels. The mixed convection air flow is used in cooling the PV panels and in generating electricity by driving the wind turbine at the duct exit. A mathematical model is proposed to describe the system hydrodynamic and thermal behavior. In addition to the mixed convection case, the pure free convection case, when there is no wind speed, has been tested. The design of the wind duct capturing system is not included in this study, which should be carefully manufactured to eliminate the reversed flow. The simulation results show that the integration of both systems not only enhances the performance of PV cell due to the effective cooling but also generates more electric power from the inserted turbine. At low wind speeds, it is found that the ducting system helps more in cooling the panels rather than driving the wind turbine. At these low wind speeds, the buoyancy effect may have a significant effect. However, at high wind speeds, the ducting system acts in both cooling the panels and driving the turbine, and at these high speeds, the buoyancy effect is insignificant.