Active Maximum Power Point Tracking Research Articles

High-efficiency hybrid PV-TEG system with intelligent control to harvest maximum energy under various non-static operating conditions

Recently the cleaner energy production is in high demand. Renewable energy systems such as photovoltaic (PV), thermoelectric generators (TEG), concentrated solar, geothermal, wind and hybrid PV-TEG systems achieved cost parity with nonrenewable fossil fuels. The power density of hybrid PV-TEG systems is much higher as compared to the standard photovoltaic (PV) or concentrated solar thermoelectric generator systems. However, the nonlinear nature of the composite hybrid power system makes it impossible to attain maximum available power using classical optimization techniques. The energy from the system is sensitive to stochastic operating conditions. Non-uniform temperature distribution (NUTD) further compromises efficiency for the available power. As a solution, a novel implementation of an arithmetic optimization algorithm (AOA) is utilized as an active maximum power point tracking (MPPT) controller for hybrid PV-TEG system power control. A comprehensive case study is made using five scenarios including real-world atmospheric data and experimental setup to validate the feasibility and effectiveness of the proposed AOA technique in real-world applications. Results are compared with highly effective intelligent techniques including grey wolf optimization (GWO), cuckoo search algorithm (CSA), particles swarm optimization (PSO), and optimized perturb and observe (P&O). Quantitative and statistical analyses confirm the robustness of the proposed technique. AOA achieves 8% higher energy and 99.86% power tracking efficiency. The tracking time in transitioning operating conditions is well within 100 ms with an average settling time of 280 ms. The results, comparative analysis, and statistical indices indicate a superior performance achieved by the proposed AOA optimization making PV-TEG a cleaner source of electrical power generation.

Simulation of large photovoltaic arrays

Large photovoltaic arrays are becoming common as the world moves to replace fossil-fuelled electricity generators. As the array size and project cost increase, it becomes increasingly important to know accurately what the array’s performance will be before it is built. Large arrays inevitably contain modules with a spread of performance characteristics such as short-circuit current and open-circuit voltage, and suffer from temperature differences between modules. In this first study of these problems, a model has been developed that accurately predicts the behaviour of a photovoltaic array subject to variability between modules and inhomogeneity of cell temperature across the array. The model was applied to a real rooftop array consisting of 912 modules (298 kW nominal peak power). Based on measured string currents, the predicted average string temperature was compared the temperature measured by a radiometric survey using a drone-mounted IR camera and matched very well.The five-parameter model of cell I-V characteristics was fitted to manufacturer’s data, with highest weighting given to the region around the maximum-power point (MPP) where a real array should operate via active MPP tracking. The model was used to explore separately the effects of a spread in module characteristics arising in the manufacturing process and of temperature inhomogeneity across the array. The current in each module of a string was constrained to be the same, and the voltage of every parallel-connected string was also constrained to be the same. These constraints lead to greater power loss than is predicted based on an average module at an average temperature. Compared to a hypothetical array assembled from identical average modules at the same average temperature, variability caused a loss of power of about 2%, depending on the detailed form of the distribution function chosen to represent the spread of characteristics in the manufacturer’s tolerance band. As a rule of thumb, de-rating the maximum power to the lower end of the manufacturer’s tolerance band is recommended to account for module variability during the design phase. The effect of temperature inhomogeneity is more serious, because temperature affects Voc strongly, causing parallel-connected strings to be pulled away from their ideal operating points to obey the constraint of equal voltage. A modest 10 °C temperature gradient across the studied array was predicted to cause about a 4% loss of power at the MPP. Much higher real temperature differences could be expected in summer and were observed. The study confirmed that temperature inhomogeneity poses a serious design problem for large arrays, requiring careful thermal design to achieve not only acceptably low average array temperature, but also the least possible temperature spread.

Topological Overview of Powertrains for Battery-Powered Vehicles With Range Extenders

The paper presents a topological overview of hybrid powertrains for battery-powered vehicles reinforced by range extenders. First, tradeoffs of employing high energy versus high power battery are revealed. Then, different topologies of battery-ultracapacitor hybrids are discussed, highlighting pros and cons of each configuration. The superiority of fully active hybrids is indicated, obtained at the expense of increase of power electronic circuitry, control effort, and efficiency. The second part of the paper focuses on two types of range extenders: renewable energy and fuel-based units. The operation strategy is shown to be different for each range extender type. The renewable-energy-based range extender should be operated employing either passive or active maximum power point tracking strategy and hence not be involved in the powertrain energy balancing. It is shown that such a strategy allows the rest of system to perceive the renewable energy range extender (RERE) as a part of the load and act accordingly. Solar array is given as an example of a RERE and the possible connection topologies are discussed. On the other hand, the fuel-based range extender (FBRE) should be operated near the lowest specific fuel consumption point employing maximum efficiency point tracking strategy. Fuel cells and internal combustion engines are specified as examples of FBREs. The complete powertrain is shown to resemble a dc microgrid with source, storage, and load units connected through power management circuitry to a common dc link.