Hybrid Wind-Solar-Storage Energy Harvesting Systems

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Date
2016
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American English
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M.S.E.C.E.
Degree Year
2016
Department
Electrical & Computer Engineering
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Purdue University
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Abstract

With the increasing demand of economy and environmental pollutions, more and more renewable energy systems with clean sources appear and have attracted attention of systems involving solar power, wind power and hybrid new energy powers[1]. However, there are some difficulties associated with combined utilization of solar and wind, such as their intermittent behavior and their peak hours mismatch in generation and consumption[1]. For this purpose, advanced network of a variety of renewable energy systems along with controllable load and storage units have been introduced[1-3].

This thesis proposes some configurations of hybrid energy harvesting systems, including wind-wind-storage DC power system with BOOST converters, solar-solar-storage DC power system with cascade BOOST converters, wind-solar-storage DC power system with BOOST converter and cascade BOOST converter, and wind-solar DC power system with SEPIC converter and BOOST converter. The models of all kinds of systems are built in Matlab/Simulink and the mathematical state-space models of combined renewable energy systems are also established. Several MPPT control strategies are introduced and designed to maximize the simultaneous power capturing from wind and solar, such as Perturb & Observe (P&O) algorithm for solar and wind, Tip Speed Ratio (TSR) control and Power Signal Feedback (PSF) control for wind, and Sliding Mode Extremum Seeking Control (SM-ESC) for wind and solar systems[4]. The control effects of some of these MPPT methods are also compared and analyzed. The supervisory control strategies corresponding to each configurations are also discussed and implemented to maximize the simultaneous energy harvesting from both renewable sources and balance the energy between the sources, battery and the load[2]. Different contingencies are considered and categorized according to the power generation available at each renewable source and the state of charge in the battery[2].

Applying the system architectures and control methods in the proposed hybrid new energy systems is a novel and significant attempt, which can be more general in the practical applications. Simulation results demonstrate accurate operation of the supervisory controller and functionality of the maximum power point tracking algorithm in each operating condition both for solar and for wind power[3]

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Indiana University-Purdue University Indianapolis (IUPUI)
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