A novel photovoltaic maximum power point tracking technique based on grasshopper optimized fuzzy logic approach

The maximum power point tracking (MPPT) in the PV system has become complex due to the stochastic nature of the load, intermittency in solar irradiance and ambient temperature. To address this problem, a novel Grasshopper optimized fuzzy logic control (FLC) approach based MPPT technique is proposed in this paper. In this proposed MPPT, grasshopper optimization is used to tune the membership functions (MFs) of FLC to handle all uncertainties caused by variable irradiances and temperatures. The performance of the proposed grasshopper optimized FLC based MPPT is studied under rapidly changing irradiance and temperature. The proposed MPPT overcomes the limitations such as slow convergence speed, steady-state oscillations, lower tracking efficiency as encountered in conventional methods viz. perturb & observed (P&O) and FLC techniques. The feasibility of the proposed MPPT is validated through experimentation. The effectiveness of the proposed scheme is compared with P&O and also with FLC MPPT.     

How can the integration of renewable energy and power-to-gas benefit industrial facilities? From techno-economic,policy, and environmental assessment

This paper applies a mixed integer linear programming model developed in GAMS to simulate the integration of Power-to-Gas infrastructure into an industrial manufacturer's energy system subject to the existing thermal and electrical energy demands, as well as a third hydrogen energy profile. This work is novel in that it assesses the challenges and economic incentives available to make feasible the installation of a hydrogen-based energy storage systems within the Province of Ontario from a techno-economic, policy and environmental perspectives.The energy hub analyzed in this work uses electricity from the power grid and solar PVs to meet the manufacturer's demands, while converting the excess to hydrogen gas, which is used across an array of pathways to generate revenue. ThisThis includes a blend ofof hydrogen for fuel cell vehicles (FCVs), hydrogen for forklifts, and the direct injection of hydrogen into the facility's natural gas, adding renewable content to the heating, and manufacturing processes. Our primary objective was to implement a safe design that minimizes capital and operating costs, resulting in a favorable business case for producing hydrogen, and providing ancillary grid services. However, Power-to-Gas creates a net-emission reduction that can be used not only to sell emission allowances in the provincial carboncarbon tax program for up to $30/t-CO_2eq but to assist the Company in achieving their strategic emission reduction targets.Installation of the selected Power-to-Gas system would require a total capital investment of $2,620,448 with the electrolyzers and solar panels accounting for 41% and 17% of the capital costs, respectively. The compressors will account for most of the operating costs which total $237,653 annually. Within the energy hub, 76,073 kg-H₂ has been produced per year for end-use applications. A sensitivity analysis was performed by varying both hydrogen and carbon credit price which predicted a potentialpotential CO₂ offset of 2359.7 tonne/yr with a payback period of as little as 2.8 years.     

Non-homogenous gamma process: Application to SiC MOSFET threshold voltage instability

The accelerated degradation tests provide the opportunity to assess the reliability of an electronic component for which only parametric degradation is observable. In the case of the silicon carbide MOSFETs, this approach makes it possible to study the impact of the threshold voltage phenomenon on the reliability of the devices. During the High Temperature Gate Bias tests, we have carried out, the threshold voltage of the ten devices under test have been monitored and their degradation modeled using a non-homogeneous Gamma process. The estimation of the degradation process parameters enable to estimate the distribution of the first hitting time to a degradation threshold which is considered as a failure criterion. Lastly, a criterion proposed by Tseng and Yu [1] has been used to provide a metric to stop these ageing tests while having relevant reliability data.     

Statistical distribution for wind power forecast error and its application to determine optimal size of energy storage system

Accurate wind power forecast is an important tool for wind farm to participate in day-ahead or hours-ahead energy markets. However, forecast errors with any methodology are so large that they cannot be neglected. The forecast error needs to be analyzed individually for single wind farm to estimate the impact of this error on trading wind energy in electricity market. Although forecast error is always assumed as normal distribution, it can be demonstrated that it is not proper with a simple statistical analysis. In this paper, a mixed distribution is proposed based on laplace and normal distribution to model forecast errors associated with persistence forecast for single wind farm over multiple timescales. Then the proposed distribution is used to estimate the penalties for prediction errors in the electricity market. Energy storage system (ESS) can smooth the wind power output and make wind power more “dispatchable”. A probabilistic method is proposed to determine optimal size of ESS for wind farm in electricity markets. The results indicate that the proposed distribution and probabilistic method is efficient to find optimal size of ESS.     

Short-term hydrothermal generation scheduling by a modified dynamic neighborhood learning based particle swarm optimization

The main objective of the short-term hydrothermal generation scheduling (SHGS) problem is to determine the optimal strategy for hydro and thermal generation in order to minimize the fuel cost of thermal plants while satisfying various operational and physical constraints. Usually, SHGS is assumed for a 1 day or a 1 week planing time horizon. It is viewed as a complex non-linear, non-convex and non-smooth optimization problem considering valve point loading (VPL) effect related to the thermal power plants, transmission loss and other constraints. In this paper, a modified dynamic neighborhood learning based particle swarm optimization (MDNLPSO) is proposed to solve the SHGS problem. In the proposed approach, the particles in swarm are grouped in a number of neighborhoods and every particle learns from any particle which exists in current neighborhood. The neighborhood memberships are changed with a refreshing operation which occurs at refreshing periods. It causes the information exchange to be made with all particles in the swarm. It is found that mentioned improvement increases both of the exploration and exploitation abilities in comparison with the conventional PSO. The presented approach is applied to three different multi-reservoir cascaded hydrothermal test systems. The results are compared with other recently proposed methods. Simulation results clearly show that the MDNLPSO method is capable of obtaining a better solution.     

Improved meta-heuristic techniques for simultaneous capacitor and DG allocation in radial distribution networks

The active and reactive power flow in distribution networks can be effectively controlled by optimally placing Shunt Capacitors (SCs) and Distributed Generators (DGs). This paper presents improved versions of three evolutionary or swarm-based search algorithms, namely, Improved Genetic Algorithm (IGA), Improved Particle Swarm Optimization (IPSO) and Improved Cat Swarm Optimization (ICSO) to efficiently handle the problem of simultaneous allocation of SCs and DGs in radial distribution networks while considering variable load scenario. The benefit of network reconfiguration has also been taken into account after optimal allocation of these devices. Several algorithm specific modifications are suggested in the standard forms of GA, PSO and CSO to overcome their inherent drawbacks. In addition, an intelligent search approach is proposed to enhance overall performance of proposed algorithms. The proposed methods are investigated on IEEE 33-bus and 69-bus test distribution systems showing promising results when compared with other recently established methods. Application results also show a marked improvement in the performance of these algorithms while compared with their respective standard counterparts.     

光纤布拉格光栅复合绝缘子的应力分布分析

为了最大程度地预防复合绝缘子芯棒脆断等掉串事故,采用在复合绝缘子芯棒中植入光纤布拉格光栅,实现对复合绝缘子芯棒应力的监测,从而判断复合绝缘子的运行状况.绝缘子芯棒在金具压接区部位的结构复杂,所受的应力分布不均匀,故不能直接用光纤光栅的自身应变来表征芯棒内部应变,因此先假设绝缘子芯棒和光纤光栅有相同的应变,对复合绝缘子芯...     

利用母线CVT响应电流实现变电站雷电侵入波在线监测

介绍了110 kV以上变电站雷电侵入波在线监测的基本原理,以及高频下电容式电压互感器(capacitor voltage transformer,CVT)回路电阻、电感、电容等值参数计算方法并通过仿真模型分析了等值参数计算误差对过电压监测的影响。提出了一种基于CVT响应电流的侵入波在线监测方法,以克服现有研究存在的不足。基于这种监测方法,开发了一种利用变电站母线CVT回路电流实现母线过电压监测的系统,通过该系统可以进行进线段侵入波电流和母线过电压的监测,实现变电站事故监测统计的自动化、智能化和信息化。最后通过电磁暂态程序(alternative transient program,ATP)仿真结果和现场运行中实测波形的对比,说明了监测系统可以持续有效运行。     

云广与贵广Ⅱ回直流输电系统共用接地极设计

为了不对系统运行产生太大影响并节省工程用地和建造费用,云广特高压直流输电工程和贵广Ⅱ回高压直流输电工程广东侧考虑采用共用接地极模式建造。根据系统运行条件、使用寿命以及人身安全的要求确定了建设共用接地极的参数,对该参数采用了矩量法和边界元法相结合的接地计算数值方法,并针对大罗州和李屋两个极址分别设计了一套共用接地极方案。这两套设计方案既能满足系统要求又能符合国家标准,不会对人身安全产生影响,可供建设共用接地极使用。     

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies.