Non-dominated sorting culture differential evolution algorithm for multi-objective optimal operation of Wind-Solar-Hydro complementary power generation system

Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.

Development modes analysis of renewable energy power generation in North Africa

North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewable energies—wind,photovoltaic(PV),and concentrating solar power(CSP)—an optimal planning model is established to minimize construction costs and power curtailment losses.The levelized cost of electricity is used as an index for assessing economic feasibility.In this study,wind and PV,wind/PV/CSP,and transnational interconnection modes are designed for Morocco,Egypt,and Tunisia.The installed capacities of renewable energy power generation are planned through the time sequence production simulation method for each country.The results show that renewable energy combined with power generation,including the CSP mode,can improve reliability of the power supply and reduce the power curtailment rate.The transnational interconnection mode can help realize mutual benefits of renewable energy power,while the apportionment of electricity prices and trading mechanisms are very important and are related to economic feasibility;thus,this mode is important for the future development of renewable energy in North Africa.

SMO Algorithm to Unravel CEED Problem using Wind and Solar

This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fuel costs and emissions.When both economics and emission tar-gets are taken into account,the dispatch of an aggregate cost-effective emission challenge emerges.This research affords a mathematical modeling-based analyti-cal technique for solving economic,emission,and collaborative economic and emission dispatch problems with only one goal.This study takes into account both the fuel cost target and the environmental impact of emissions.This bi-inten-tion CEED problem is converted to a solitary goal function using a price penalty factor technique.In this case,a metaheuristic and an environment-inspired,intel-ligent Spider Monkey Optimization technique(SMO)are used to address the CEED dilemma.By following the generator’s scheduling process,the SMO meth-od is used to regulate the output from the power generation system in terms of pollution and fuel cost.The Fission-Fusion social(FFS)structure of spider mon-keys promotes them to utilize a global optimization method known as SMO dur-ing foraging behaviour.The emphasis is mostly on lowering the cost of generation and pollution in order to improve the efficiency of the power system and han-dle dispatch problems with constraints.The economic dispatch has been reme-died,and the improved result demonstrates that the system’s performance is stable andflexible in real time.Finally,the system’s output demonstrates that the system has improved in resolving CEED difficulties.When compared to ear-lier investigations,the proposed model’sfindings have improved.As the gener-ating units,wind and solar are used to explore the CEED crisis in the IEEE 30 bus system.

Simulation Analysis for Massive Deployment of Variable Renewables Employing an Optimal Power Generation Mix Model

This paper develops a high time-resolution optimal power generation mix model in its time resolution of 10 minutes on 365 days by linear programming technique. The model allows us to analyse the massive deployment of photovoltaic system and wind power generation in power system explicitly considering those short-term output variation. PV （photovoltaic） and wind output are estimated, employing meteorological database. Simulation results reveal that variable fluctuation derived from a high penetration level of those renewables is controlled by quick load following operation of natural gas combined cycle power plant, pumped-storage hydro power, stationary NAS （sodium and sulfur） battery and the output suppression control of PV and wind. It additionally turns out that the operational configuration of those technologies for the renewable variability differs significantly depending on those renewable output variations in each season and solving the seasonal electricity imbalance as well as the daily imbalance is important if variable renewables are massively deployed.

Hybrid PV/Wind/Diesel Based Distributed Generation for an Off-Grid Rural Village in Afghanistan

Afghanistan has a tremendous resource potential of renewable energy especially solar and the wind. Therefore, utilization of these resources has a special rule for the remote areas where access to the electrical grid or secure power supply is a dream for most of the people. This paper presents a feasibility and usefulness of hybrid power generation based on PV/wind/diesel generator for an off-grid rural village that feeds the load at a rate of average 7.9 kWh/day with 1.32 kW peak load. GsT （geospatial toolkit） is used to obtain the solar and wind data of the site. Windographer software is used to analyze the wind resource data of the site. HOMER Pro software package is used to select the suitable and reliable hybrid generation system and calculate the optimal capacities and costs of the components. Through the study, it is found that this state of the art adaptation could provide vast opportunities for off-grid rural communities such as in Afghanistan where enough high penetration of renewable energy is available.

Renewable Energy:Wind Turbines,Solar Cells,Small Hydroelectric Plants,Biomass,and Geothermal Sources of Energy

In this paper,we present five basic types of renewable energy sources,namely:wind turbines,solar cells,small hydroelectric plants,biomass,and geothermal sources of energy.Wind turbines transform energy of wind into electrical energy,solar cells transform energy of sun into electric energy,hydroelectric plants transform energy of water into electric energy,devices or machines can be constructed to transform energy of biomass into heat energy,and geothermal energy into some form of energy.In this paper we present basic information and reasons why there is need today to use these forms of energy—called green energies,we present how these devices or machines function,and we propose for future work design of typical devices or machines that will satisfy basic functional needs.

A Simulation Research on the Grid-Connected Control Technology of Single-Phase Inverters Based on MATLAB

This paper primarily discusses the main circuit of single-phase inverter circuits.It begins by introducing the research context and the significance of the subject,then discusses the topology of grid-connected single-phase inverter circuits,continues by discussing the control strategy for grid-connected single-phase inverter circuits,realizes a sinusoidal pulse width modulation(SPWM)signal generation circuit and an inverse control algorithm program,and finally ensures good output waveform and fast dynamic response.In view of the hysteresis feature of the grid voltage’s synchronous signal sampling circuit,the acquisition function in digital signal processing(DSP)control chips is applied,and the reasons for the hysteresis phenomenon are thoroughly investigated.The reliability of the SPWM control algorithm is revealed through the results.

风光热储互补发电系统容量配置技术研究

针对无常规电源支撑的风光热储互补发电系统,协调规划装机容量对提高发电系统运行经济性和利用率具有重要意义。提出了一种双层优化配置方法,上层以最小度电成本及弃电率为目标,确定系统装机容量;下层以新能源发电消纳最大为目标,解决功率分配问题。通过反复迭代寻优,得到系统容量配置;然后;通过纳什谈判对优化结果进行选择;最后,对甘肃河西地区数据进行仿真分析。结果表明:风光热储互补发电系统最优容量配置下的度电成本为0.3064元/(k W·h);风电场加光伏电站装机容量与光热电站装机容量的最优比为6:1,对比相同装机容量的风光互补发电系统,风光热储互补发电系统具有更高的稳定性。

公路隧道风光水储互补发电系统容量配置研究

为降低公路隧道的电力运营成本,探究可再生能源互补发电系统在公路隧道的应用前景,研究合适的容量配置求解方法。建立利用风、光、水和储能设备的互补发电系统为公路隧道提供电力资源。以特长公路隧道(总长7.1 km)为估算模型,采用改进后的粒子群优化算法,即离散型自适应粒子群优化算法,以全生命周期的建设成本和设备维护成本最小为目标函数,以缺电负荷率(LPSP)和储能电池的状态为约束,对风力发电设备、光伏发电设备、水力发电设备和储能设备的最优容量配置进行求解。结果表明:1)对比标准粒子群算法,离散型自适应粒子群优化算法的总投入成本更少,寻优能力更强;2)对比该隧道1年的用电成本,前期投入将在5年内回本;3)在风光水储互补发电系统的设备全生命使用周期的20年内,该隧道可节省1 920.39万元电费。

风光互补发电系统混合储能系统容量优化方法研究

风光互补发电系统受风光资源影响发电功率波动较大,配置适当的储能系统可提高新能源发电的消纳能力和电能质量。针对风光互补发电系统储能容量优化配置问题,将运行投入成本作为优化目标,提出以抽水蓄能为基础,蓄电池和超级电容参与的混合储能系统模型。该储能模型以跟踪负荷曲线作为平抑目标函数,利用集合经验模态分解和滑动平均法,对抽水蓄能机组、蓄电池和超级电容设备进行功率分配。建立了风光发电系统模型,利用带免疫的粒子群算法对储能配置容量进行寻优求解。计算结果表明,所提基于抽水蓄能的混合储能容量优化模型,对发电系统输出功率波动情况改善明显,电能消纳能力和运行经济性有所提高。

水火风光多能互补系统联合调度问题两层优化建模方法研究

为解决水火风光多能互补发电系统联合优化复杂问题,提出了一种水火风光多能互补系统联合调度问题两层优化建模和求解方法,上层以余荷均方差和期望均值最小为目标函数对水风光清洁能源打捆进行联合优化,下层以成本经济指标最小为目标函数对火电适配余荷进行优化。以江西省典型春秋季、夏季和冬季江西省的电网负荷以及风电、光电的出力过程为研究对象进行实例分析,采用研究团队提出的DPSA-POA和智能算法混合优化方法进行模型求解,验证了本文所提两层优化建模和求解方法的有效性。并发现了风光可弃情境相比风光完全消纳情景虽然在火电出力上有所提高,但在整体运行费用上有所降低。在以春秋季江西省的电网负荷和风电、光电的出力过程为研究对象进行的实例分析结果显示,火电出力总和提升了5.79%,多能互补系统整体运行费用减少了4.97%;在以夏季江西省的电网负荷和风电、光电的出力过程为研究对象进行的实例分析结果显示,火电出力总和提升了0.32%,多能互补系统整体运行费用减少了1.95%;在以冬季江西省的电网负荷和风电、光电的出力过程为研究对象进行的实例分析结果显示,火电出力总和提升了10.70%,多能互补系统整体运行费用减少了6.78%。该方法为求解水火风光多能互补联合优化复杂问题提供了一种新的思路。

计及风光出力相关性的风光水储互补系统优化调度

由于风电、光电及水电出力均具有随机性、波动性等特点,其大规模投入电网所带来的不确定性成为目前多能互补系统研究的难点。对此,构建了以抽蓄电站为储能装置的风光水储互补系统,为充分考虑风光出力的不确定性与相关性,采用Frank-Copula联合概率分布函数生成风光出力场景;在水电站丰平枯时期不同出力特性下综合考虑系统各约束,以互补系统出力波动性最小为目标建立优化调度模型,并采用遗传算法进行求解;最后通过算例分析验证了所提模型的有效性,结果显示在引入抽水蓄能电站后,系统的波动性都有所降低,其中丰水期降低了12.65%,平水期降低了15.79%,枯水期降低了24.26%,这表明风光水储互补系统可以减少风电、光伏发电及水电的波动性对电网的影响。

基于改进NSGA-Ⅱ算法的风光互补发电系统储能控制优化

风光互补技术带来了稳定的能源储存,但同时也存在着能量密度低及时间地区分布杂乱等问题。因此,现提出基于改进NSGA-Ⅱ算法的风光互补发电系统储能控制优化方法。基于改进NSGA-Ⅱ算法构建储能模型,保留多种能量存储单元特点,能够高效、可靠地保证风光互补发电系统的供电可靠性;风光互补发电系统的能源转换,可以优化风光互补发电系统的容量。实验结果表明:提出的基于改进NSGA-Ⅱ算法的风光互补发电系统储能控制优化方法的平均储能功率为2.35 MW,方法 1的平均储能功率要远远小于所提出的方法,证明所提出的风光互补发电系统储能控制优化方法具有重要的实际应用价值。

严寒地区宜居低碳牧居建筑设计

为改善捡烧牛粪燃能的利用方式,探索广大高原严寒牧区牧民住房绿色低碳转型路径,释放放牧草地生态系统蕴含的巨大减排增汇潜力和价值,文中以装配式低碳牧居替代捡烧牛粪的帐篷为导向,综述了近年来国内外严寒牧区牧民住房在装配式建筑、骨架与围护结构、光风互补供电系统和太阳能供暖系统四个方面绿色低碳技术的进展与态势,结合牧户调查、技术研发和牧居示范工程建设的实践,归纳、探讨了净零碳排放牧居技术路径,解析了取得初步成果的主要参数、经验和不足,为严寒地区牧居低碳化设计提供借鉴。得出“三室一廊”牧居、装配式骨架结构、低能耗围护结构、可再生能源替代和精细化管理可能成为牧区人与自然和谐共生现代化中新一代牧居的美好图景的结论。

变时间尺度的风光互补发电短期功率预测技术

该文探究适用于风光互补发电系统的变时间尺度短期功率预测技术。风力发电机组的功率预测模型以风速作为输入参数,光伏发电机组的功率预测模型以温度和光照强度作为输入参数。经过数据校正模块、地形变化模块、辐射量计算模块、功率预测模块的处理后,准确预测输出功率。在此基础上使用Simulink仿真软件构建风光互补发电模型,采集一天的风速和太阳能辐射数据作为输出量,仿真结果表明该模型的实际输出功率和期望输出功率基本一致,变时间尺度的短期功率预测技术达到预期效果,有助于实现风光互补发电系统的可靠并网。

风光互补发电在污水处理厂的研究和设计

风光互补发电是以风力资源和太阳能资源为基础的互补性发电方式,在现代社会中具有不可替代的优势。全文利用文献研究法,立足于污水处理厂视角,首先针对性地从风力发电部分、太阳能发电部分分析风光互补发电系统的组成结构,最后以山丹县污水处理厂为例,结合改造工程对风光互补发电系统的应用效果进行分析。

风光互补发电系统在水产养殖中的应用分析

在介绍风光互补发电系统组成、工作原理及过程的基础上,讨论了风光互补发电系统在水产养殖区的应用和优势,通过计算养殖场用电量、电网用电成本、风光互补发电系统发电量、建设成本,从经济效益、安全环保等方面,分析了风光互补发电系统在水产养殖中的可行性,指出风光互补发电系统利用风能和太阳能的互补性,很好地解决了水产养殖场的用电需求,是一种适合在水产养殖区域应用的理想的能源技术,具有较高的实际应用价值。

风光互补发电系统的功率优化调度与协调控制策略研究

风光互补发电系统在低风速或低光照条件下,通过光伏与风电互补,有效弥补了单一能源发电的不足,显著提高了整体发电效率。在不同太阳辐照度和风速条件下,通过优化调度与控制策略,系统的发电效率波动范围被有效控制在较小区间内。本研究提出的风光互补发电系统功率优化调度与协调控制策略能有效提高发电效率,减少能源浪费,为可再生能源的高效利用提供新的解决方案。

分水闸门采用直流供电系统的设计研究

水利输水工程中采用风光互补直流供电的闸门测控系统已在国内诸多输水工程项目中开展了试验性应用,系统采用直流直驱方式进行闸阀门监控,系统配备视频监控、水情、水力监测、信息化传输等功能的系统化输水测控方案已得到较为成熟的应用,并具备推广应用条件,系统的新能源供电和直流直驱闸门测控方案可有效解决水利工程存在的市电供应成本高、安全环保成本大、管理维护困难等突出问题,为有效推进水利信息化建设提供了基础保障,对智慧水利建设提供了技术支撑,为分析风光互补供电的直流闸门测控系统特征,在工程实际项目中进行针对性地系统设备选型,通过实际系统工程建设、试验运行,表明风光互补供电的闸门测控系统可实现稳定运行要求,在特定环境和设计配置使用条件下有必要进行针对性设计选型。

基于风光互补供电的输电线路在线监测系统研究

面对全球能源危机和环境保护的双重压力,风能和太阳能作为主要的可再生能源,因其清洁、无限等特性而备受关注。但这2种能源的不连续性和不稳定性限制了其广泛应用。鉴于此,提出了一种基于风光互补供电的输电线路在线监测系统。该系统利用风能和太阳能的互补特点,提供一种稳定的电源供应方案。其不仅能够保障输电线路监测设备的持续运行,实现输电线路的实时、高效监测,还能减少化石能源的使用,降低环境污染,对推动电力系统的绿色可持续发展具有积极作用。