Analysis of parabolic through collector cleaning system under adaptive scheduling policy
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The purpose of this study is to investigate the effects of stochastic dust accumulations and rain events on the cleaning schedule of the parabolic trough collectors that are used to generate power at concentrated solar power (CSP) plants. The level of cleanliness is proportional to the power produced, and thus it affects the economic pay off at CSP plants. Current practice to address this dust problem, termed as conventional cleaning, is to follow a periodic cleaning schedule that entails a fixed setup cost for each cleaning event. The frequency of cleaning under such conventional (periodic schedule) policy is selected based upon a tradeoff between the set up cost and the payoff from improving the cleanliness factor. The conventional practice is to have a constant and periodic cleaning schedule over an entire season (e.g. either severe or mild combination of the dust and rain over a 180-day cleaning season, with either 8 or 4 cycles scheduled for the severe and mild seasons respectively). This thesis draws upon evidence from recent literature to show that presence of random rain events improves the cleanliness of parabolic troughs in CSP plants. Upon analyzing such evidence, this study models rain event as a compound Poisson process that replenishes the level of cleanliness. In this scenario, it is possible to establish an adaptive threshold policy for scheduling plant cleaning that analogous to the formulation of a (s,S) inventory management policy, subject to random replenishment of inventory. The study offers a review of related literature to establish that such formulations are not amenable to a close form solution. The second half of the thesis describes a numerical study that has been conducted using Arena Simulation package for characterizing the adaptive cleaning policy. The parameter of interest for assessing system performance is the average payoff over the average cost of cleaning for a 180-day cleaning season. Numerical study shows that adaptive cleaning policy outperforms the conventional (periodic) cleaning policy under reasonable assumptions for dust and rain event distributions. As an extension, the simulation study also examines the use of alternative cleaning system, known as electrodynamic screening (EDS), for different rain scenarios that may be used in conjunction with either conventional or adaptive cleaning policies to improve the overall system performance.
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