Maximum power principle

About: Maximum power principle is a research topic. Over the lifetime, 14152 publications have been published within this topic receiving 207723 citations.

Comparative study of maximum power point tracking algorithms using an experimental, programmable, maximum power point tracking test bed

Abstract: Maximum power point tracking (MPPT) is important in solar power systems because it reduces the solar array cost by decreasing the number of solar panels needed to obtain the desired output power. Several different MPPT methods have been proposed, but there has been no comprehensive experimental comparison between all the different algorithms and their overall maximum power point (MPP) tracking efficiencies under varying conditions (i.e. Illumination, temperature, and load). This paper such a comparison. Results are using a microprocessor controlled MPPT powered by a 250 W photovoltaic (PV) array and also a PV array simulator.

Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System

Abstract: A new fuzzy-logic controller for maximum power point tracking of photovoltaic (PV) systems is proposed. PV modeling is discussed. Conventional hill-climbing maximum power-point tracker structures and features are investigated. The new controller improves the hill-climbing search method by fuzzifying the rules of such techniques and eliminates their drawbacks. Fuzzy-logic-based hill climbing offers fast and accurate converging to the maximum operating point during steady-state and varying weather conditions compared to conventional hill climbing. Simulation and experimentation results are provided to demonstrate the validity of the proposed fuzzy-logic-based controller.

Nanoscale heat engine beyond the Carnot limit.

Abstract: We consider a quantum Otto cycle for a time-dependent harmonic oscillator coupled to a squeezed thermal reservoir. We show that the efficiency at maximum power increases with the degree of squeezing, surpassing the standard Carnot limit and approaching unity exponentially for large squeezing parameters. We further propose an experimental scheme to implement such a model system by using a single trapped ion in a linear Paul trap with special geometry. Our analytical investigations are supported by Monte Carlo simulations that demonstrate the feasibility of our proposal. For realistic trap parameters, an increase of the efficiency at maximum power of up to a factor of 4 is reached, largely exceeding the Carnot bound.

Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review

Abstract: In recent years there has been a growing attention towards use of solar energy. The main advantages of photovoltaic (PV) systems employed for harnessing solar energy are lack of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behavior of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. A variety of MPPT methods have been proposed and implemented. This review paper introduces a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods. This classification, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions. Some of the methods from each class are simulated in Matlab/Simulink environment in order to compare their performance. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.

Maximum Power Point Tracking of Multiple Photovoltaic Arrays: A PSO Approach

Abstract: Multiple photovoltaic (PV) modules feeding a common load is the most common form of power distribution used in solar PV systems. In such systems, providing individual maximum power point tracking (MPPT) schemes for each of the PV modules increases the cost. Furthermore, its v-i characteristic exhibits multiple local maximum power points (MPPs) during partial shading, making it difficult to find the global MPP using conventional single-stage (CSS) tracking. To overcome this difficulty, the authors propose a novel MPPT algorithm by introducing a particle swarm optimization (PSO) technique. The proposed algorithm uses only one pair of sensors to control multiple PV arrays, thereby resulting in lower cost, higher overall efficiency, and simplicity with respect to its implementation. The validity of the proposed algorithm is demonstrated through experimental studies. In addition, a detailed performance comparison with conventional fixed voltage, hill climbing, and Fibonacci search MPPT schemes are presented. Algorithm robustness was verified for several complicated partial shading conditions, and in all cases this method took about 2 s to find the global MPP.