Battery-Free Power Supply for Wireless Sensor Combining Photovoltaic Cells and Supercapacitors

This article exhibits the sizing, modelling, and characterization of a power supply (output 3.3 V, 200 mA max, 11 days full autonomy) dedicated to powering a wireless sensor node without a battery but usable as simply as with a battery. This system is modular for various light levels (indoor and outdoor). It is easily integrable into a sensor node, using only commercial circuits. The choices of the photovoltaic surface (amorphous silicon, η 5%, 35 cm2) and of the supercapacitors value (2x 25F, 2.7 V) are explained for permanent operation, considering the solar potential and the consumption. An original part of the paper is devoted to the issue of the startup, in which we demonstrate that after a particular preload, once installed, the device can start on request at the desired time (within 15 days) using as a trigger any light source, such as the LED of a mobile phone.

Study and Implementation on Batteries Charging Method of Micro-Grid Photovoltaic Systems

In the micro-grid photovoltaic systems, the random changes of solar radiation enable lead-acid batteries to experience low SOC (State of Charge) or overcharged for periods of time if directly charged with such traditional methods as decreased charging current, which will reduce lifetime of batteries. What’s more, it’s difficult to find a proper reduction coefficient in decreasing charging current. To adapt to the random changes of circumstance and avoid selecting the reduction coefficient, a new fast charging method named decreased charging current based on SOC is proposed to apply into micro-grid photovoltaic systems. It combines batteries’ SOC with the maximum charging voltage to determine the charging rate without strictly selecting reduction coefficient. By close-loop current control strategy and related scheme, the experiment proves the new method is feasible and verifies that, comparing with decreased charging current, the improved method make batteries’ SOC reach 100% in shorter time as well as the temperature of batteries raise more slowly.

A novel coordinated control strategy considering power smoothing for a hybrid photovoltaic/battery energy storage system

This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emergency conditions. When the system is grid-connected, BES regulates the fluctuated power output which ensures smooth net injected power from the PV/BES system. In islanded operation, BES system is transferred to single master operation during which the frequency and voltage of the islanded microgrid are regulated at the desired level. PSCAD/EMTDC simulation validates the proposed method and obtained favorable results on power set-point tracking strategies with very small deviations of net output power compared to the power set-point. The state-of-charge regulation scheme also very effective with SOC has been regulated between 32% and 79% range.

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.

Optimal Design of Photovoltaic–Battery Systems Using Interval Type-2 Fuzzy Adaptive Genetic Algorithm

Many countries have been triggered to provide a new energy policy which promotes renewable energy applications because of public awareness to reduce the global warming and rising in fuel prices. Renewable energy sources such as solar energy are green and promising energy in the future for widespread use. Combining renewable energy sources with battery makes electricity supply more economical and reliable to meet all possible load level. This paper proposed a new hybrid method to optimize Photovoltaic (PV)-Battery systems. The proposed method was named Interval type-2 fuzzy adaptive genetic algorithm (IT2FAGA). Genetic algorithm (GA) is one of modern optimization techniques that has been successfully applied in various areas of power systems. To enhance the ability of GA to prevent trapping in? local optima and increase convergence in a global optima, the crossover probability (pcross) and the mutation probability (pmut), parameters in GA, are tuned using interval type-2 fuzzy logic (IT2FL). Objective function used in this paper was the annual cost of sytem (ACS) consisting of the annual capital cost (ACC), annual replacement cost (ARC), annual operation cost maintenance (AOM). The proposed method was also compared to fuzzy adaptive genetic algorithm (FGA) and standard genetic algorithm (SGA). Simulation results indicated that the

A Robust Single-Sensor MPPT Strategy for Shaded Photovoltaic-Battery System

A robust single-sensor global maximum power point tracking(MPPT)strategy based on modern optimization for photovoltaic systems considering shading conditions is proposed in this work.The proposed strategy is designed for battery charging applications and direct current(DC)microgrids.Under normal operation,the curve of photovoltaic(PV)output power versus PV voltage contains only a single peak point.This point can be simply captured using any traditional tracking method like perturb and observe.However,this situation is completely different during the shadowing effect where several peaks appear on the power voltage curve.Most of these peaks are local with only a single global.This condition leads to the incapability of traditional tracking approaches to extract the global peak power due to their inability to distinguish between the local and global peak points.They are trapped in the first peak point even when the point is local.Therefore,global tracking approaches based on modern optimization are highly required.A recent marine predators algorithm(MPA)has been used to solve the problem of tracking the global MPP under shadowing influence.Different shadowing scenarios are used to test and evaluate the performance of MPA based tracker.The obtained results are compared with particle swarm optimization(PSO)and ant lion optimizer(ALO).The results of the comparison con-firmed the effectiveness and robustness of the proposed global MPPT-MPA based tracker over PSO and ALO.

A review on capacity sizing and operation strategy of grid-connected photovoltaic battery systems

Due to the fluctuation and intermittency of distributed PV generation,battery energy storage is required with higher renewable installation towards carbon neutrality.Thus,the photovoltaic battery(PVB)system receives increasing attention.This study provides a critical review on PVB system design optimization,including system component sizing and strategy improvement studies,from mathematical modeling,evaluation system establish-ment to feasibility and optimization studies.Several PVB simulation software packages are compared and eval-uated,and acknowledged system models are presented.The evaluation indicators are summarized from various aspects with cases of various evaluation systems combining different indicators or using the Pareto front for multi-criteria system designing.The PVB system feasibility study is analyzed from system configuration varia-tion,critical technical and economic parameter analyses,rule-based operation strategies to future expectations like large-scale energy storage profitability,grid parity,and energy community trading platform.The targets,methods,tariffand time resolution influences,and PVB system capacity optimization design recommendations are critically discussed.The research directions for system operation development and future expectations are analyzed from system feasibility,flexibility to resilience.The co-planning of PVB system capacity and operation design optimization makes the problem complicated,leading to relatively short time resolution but more flexi-bility to system operation strategy.This study could provide guidance and references to distributed PVB system future design and optimization studies.

Deep reinforcement learning for online scheduling of photovoltaic systems with battery energy storage systems

A new online scheduling algorithm is proposed for photovoltaic(PV)systems with battery-assisted energy storage systems(BESS).The stochastic nature of renewable energy sources necessitates the employment of BESS to balance energy supplies and demands under uncertain weather conditions.The proposed online scheduling algorithm aims at minimizing the overall energy cost by performing actions such as load shifting and peak shaving through carefully scheduled BESS charging/discharging activities.The scheduling algorithm is developed by using deep deterministic policy gradient(DDPG),a deep reinforcement learning(DRL)algorithm that can deal with continuous state and action spaces.One of the main contributions of this work is a new DDPG reward function,which is designed based on the unique behaviors of energy systems.The new reward function can guide the scheduler to learn the appropriate behaviors of load shifting and peak shaving through a balanced process of exploration and exploitation.The new scheduling algorithm is tested through case studies using real world data,and the results indicate that it outperforms existing algorithms such as Deep Q-learning.The online algorithm can efficiently learn the behaviors of optimum non-casual off-line algorithms.

Off-Grid Photovoltaic System Design for Haiti School Project

In this paper a Photovoltaic (PV) system was designed for the Port-Margot School Solar Project in Haiti. This off-grid system consists of PV panels, inverter, battery storage and other components such as fuses, dc/ac disconnects and transformers [1]. Sizing the PV to fit on the roof was determined. The battery storage and inverter were chosen to be installed in the school building. The expected energy production was compared with data file from NASA website. The KW PV system was chosen to be the most effective and demonstrating renewable technologies and reducing the electrical load of the school.

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.

Modeling and Experimental Verification of Electric Vehicles Off-Grid Photovoltaic Powered Charging Station

With the increasing development of EVs, the energy demand from theconventional utility grid increases in proportion. On the other hand, photovoltaic(PV) energy sources can overcome several problems when charging EVs from theutility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and alead-acid battery representing the energy storage system (ESS). A bidirectionalDC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PV and regulate the DC-linkvoltage. It also controls the voltage and current levels of both the ESS and the EVduring the charging/discharging process. The study has been applied to two caseswith different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verifythe system performance, experimentally. Design guides for higher power levelsare proposed to help in choosing the proper parameters of the converters. Boththe simulation and experimental results are matched and verify the highperformance of the proposed system.

Comparison between SiC- and Si-Based Inverters for Photovoltaic Power Generation Systems

100-W class power storage systems were developed, which comprised spherical Si solar cells, a maximum power point tracking charge control-ler, a lithium-ion battery, and one of two different types of direct current (DC)-alter- nating current (AC) converters. One inverter used SiC met-al-oxide-semicon-ductor field-effect transistors (MOSFETs) as switching devices while the other used Si MOSFETs. In these 100-W class inverters, the ON resistance was considered to have little influence on the efficiency. Nevertheless, the SiC-based inverter exhibited an approximately 3% higher DC-AC conversion efficiency than the Si-based inverter. Power loss analysis indicated that the higher efficiency resulted predominantly from lower switching and reverse recovery losses in the SiC MOSFETs compared with in the Si MOSFETs.

光伏硅弃料制备锂离子电池硅负极的性能

纯硅的导电性差,且纳米化、非晶化技术成本高。光伏行业用硅的产业化程度高、导电性好,弃料可在锂离子电池硅基负极实现再利用。以光伏硅弃料为原料,采用机械球磨法制备纳米硅和非晶/纳米硅材料。制备的材料均具有较高的可逆比容量和稳定的循环性能,以0.2 C在0.005~0.900 V循环100次,纳米硅剩余的比容量为2 123.32 mAh/g,非晶/纳米硅剩余的比容量为1 367.70 mAh/g。

计及储能电池寿命衰减的居民小区光储优化配置

在居民小区配置光伏系统可减小电力系统的供电压力,配置储能装置能够减小光伏弃光率,同时还可以实现负荷的时空转移,减小负荷峰谷差。为使居民小区光储系统的配置更加合理,利用充放电次数和放电深度对储能电池寿命的影响,通过改进曲线拟合方法及线性分段处理方法,获得更加准确的曲线拟合函数和与原曲线更加贴合的分段线性函数,建立储能电池动态损耗模型;以光储系统年均净收益最大和负荷峰谷差最小为目标函数,对光储系统进行优化配置;最后使用不同权重求解方法得到光伏出力值及负荷需求值,采用多目标粒子群算法对在不同运行场景下的居民小区光储系统配置问题进行求解,并通过仿真对比分析不同运行场景下光储系统的运行策略。结果表明,居民小区储能系统在并网场景下的经济性和削峰填谷效果更佳,所采用模型合理有效,可为居民小区光储系统的规划建设提供参考。

离网型风光储微电网控制策略研究

为了解决偏远地区电力供应不足的问题,笔者提出一种含风力发电、光伏发电及蓄电池储能的离网型风光储微电网系统。风力发电最大功率点跟踪(maximum power point tracking,MPPT)采用叶尖速比法的控制策略,光伏发电MPPT采用变步长扰动观察法的控制策略,蓄电池储能系统采用基于双闭环控制的充放电控制策略。结合广西地区实际风速及光照强度变化情况,利用MATLAB/Simulink平台对所提出的风光储微电网系统进行了建模及仿真,验证了所提系统的可靠性和控制策略的有效性。

考虑电化学模型的配电网侧光储系统分布式优化调度

配电网侧广泛接入的光储系统具备成为电网调度中灵活性资源的潜力。为了提高光储系统调控的精细程度,分析建模了光储系统运行的动态特性,构建了考虑电化学模型的光储调度模型。针对保护节点用户隐私和调用分布式计算资源的需求,根据该光储调度模型给出了适用于计算的矩阵化形式,并构建了各节点处含光储系统的配电网调度优化的分布式子问题,实现了该调度优化问题的分布式求解。基于IEEE 33节点系统算例验证了所提方法的有效性。结果表明,该方法给出的调度方案在可行性、储能运行高效性和老化衰退抑制能力等方面具有优势。

从BIPV(光伏建筑一体化)到BIPVES(光伏储能建筑一体化)

[目的]随着光伏、储能、新型建材及装配式建筑产业的发展,将光伏组件与屋面、墙体、遮阳等构件进行一体化设计与制造的光伏建筑一体化(Building Integrated Photovoltaic,BIPV)技术开始延伸为光伏储能建筑一体化(Building Integrated Photovoltaic and Energy Storge,BIPVES)技术。[方法]文章提出世界首个可充电水泥电池,将建筑墙体与光伏发电装置、储放电装置相融合;对设备和材料进行跨界创新,在玻璃表面打印高清晰度、高透光率花纹图案,制造高效光伏建材;研发预制式储能墙体,与各类钢结构装配式建筑体系进行结合,实现订制式生产、装配式施工,形成建筑构件与光伏、储能一体化的变革趋势。[结果]水泥基电池实现了建筑墙体具有光伏发电、储电以及供电等多种功能;新一代光伏建材可节省建筑外立面装饰材料的成本,降低建筑物碳排放;光伏和储能等可再生能源技术在建筑中的一体化集成,可取得最大化收益。[结论]新型光伏建材技术和水泥电池等新型储能技术具有发展前景,将可充电电池构件、光伏外墙板与装配式建筑墙体及预埋件进行组合集成并推广应用具有可行性。

光储系统并网功率波动平抑及储能优化配置

【目的】电池储能是保证光伏发电系统可靠性、提高光伏发电利用率的有效手段之一,但在光储电站中存在功率波动平抑难、储能容量配置不合理等问题,为解决这些问题,开展了相关研究。【方法】针对能量型电池储能,分析了调度模式和自主模式特性,提出了一种基于储能运行在调度模式的光储系统限功率平抑策略,以实现功率平抑和减少储能充放电频繁切换。建立了以最小光储系统弃电损失为优化目标,以功率波动越限概率等作为约束条件的优化模型,并利用算法对储能配置进行求解和优化。以西藏朗明桑珠孜50 MW光储电站为例,验证了所提平抑策略的有效性。【结果】所提平抑策略在不增加储能充放电切换次数的前提下,将光储系统并网功率波动越限概率由25.64%降至6.41%,且并网功率波动越限概率为5%时,该50 MW并网光伏电站储能系统最优配置为14.5 MW/94 MW·h。【结论】所提抑策略及储能优化配置方法可为并网光储电站优化设计和运行提供技术参考。

新能源产业链构建:光伏发电-电化学储能-新能源汽车

以高速路网光伏发电-电化学储能-新能源(电)汽车全产业链为基础,描述未来新能源生态体系的构筑蓝图:①在供给侧,探讨全面普及清洁能源的战略布局,打造高速路网光伏超级电站,依托光伏发电全生命周期低成本的优势,直接为下游终端提供电力,大幅降低新能源应用端的使用成本,推动以新能源汽车为中心的下游产业扩张,减少传统能源消耗和碳排放,助推绿色发展;②在储能端,加速液流电池和液态金属电池等电网储能设备的应用以及以硅碳和三元材料为代表的高容量动力电池材料的规模化生产进程,统一电池和配套设施的制造标准,并借助互联网战略,建立电池全生命周期的监测、维护和回收利用网络;③在应用端,制定新能源汽车的全新制造标准,全面推行模块化的设计和生产,用可更换电池模组替代集成式电池模组,建设替代加油站的配套电池供应网络,提供电力接入和电池充电、更换、维护服务。另外,还简述了利用新能源产业中的弃风、弃光发展氢能源,以氢能作为当下新能源体系的补充。通过新能源产业上、中、下游的同步建设,希望在未来30年内打造一个供给端-储能端-应用端协同发展的产业链,逐步形成独立于化石能源的、包含光伏和风电等多种能源形式的新能源闭环生态体系,实现社会能源消费结构转型,助力“碳达峰、碳中和”战略实施。

纳米流体电池热管理研究进展

随着非化石能源的开发利用,各行业电气化程度的提高以及储能技术的发展,各种电池的应用越来越广泛,同时电池向着高能量密度方向发展.在充放电过程中,电池组内能量密度的上升导致电池过热乃至爆炸,进而影响电池组的寿命和安全.因而,亟待开发高效的热管理系统,以及时带走电池内的热量.近年来,多种新型热管理系统被广泛研究和应用.其中,具有效果显著、成本低廉和无额外能耗等优势的纳米流体电池热管理系统备受关注.本文对纳米流体电池热管理系统的研究进展进行了系统综述,首先介绍了常见的电池种类及常用的热管理技术,随后阐述了纳米流体的分类和性质,并详细论述了纳米流体在锂离子电池、燃料电池和太阳能电池三类电池中的热管理理论、数值模拟、实验和应用研究现状.最后,本文系统讨论了当前该领域面临的挑战,并提出了未来的发展方向.