Combining of Renewable Energy Plants to Improve Energy Production Stability Public
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This thesis details potential design improvements by exploiting a new general grid model utilizing multiple wind and solar energy plants. A single renewable energy plant which relies on wind speed or solar insolation is unreliable because of the stochastic nature of weather patterns. To allow such a plant to match the requirements of a variable load some form of energy storage must be incorporated. To ensure a low loss of load expectation (LOLE) the size of this energy storage must be large to cope with the strong fluctuations in energy production. It is theorized that by using multiple renewable energy plants in separate areas of a region, the different weather conditions might approach a probabilistically independent relationship. The probability of energy generated from combined plants will then approach a Gaussian distribution by the central limit theorem. While maintaining the same LOLE as a single renewable plant this geographic separation model theoretically stabilizes the energy production and reduces the system variables: energy storage size, energy storage efficiency, and cumulative plant capacity. New generic weather models that incorporate levels of independence are created for wind speeds and solar insolations at different locations to support the geographic separation model. As the number of geographically separated plants increases and the weather approaches independence the system variables are reduced.
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