Question

What are the riisk and uncertainty of

1 solar photovoltaic (PV)

2 Power souce Diesel Engines

Answer 1

Solution:

1A)The revenues generated by rooftop photovoltaic (PV) systems have several sources of uncertainty. We use a Monte Carlo framework to explore the sensitivity of PV investment returns to three categories of PV investment uncertainty:

1) interannual solar variability,

2) PV technical performance and maintenance costs,and

3) market risks including future electricity rates and the possibility that retail electricity rates will be restructured for PV customers. We find that PV investment risk and uncertainty is driven by market factors in some U.S. regions (California and Massachusetts) and by the PV technical performance in other U.S. regions (Missouri and Florida). We explore the relative impacts of three methods for reducing PV investment uncertainty: research-and-development-driven performance improvements, system performance guarantees that are common for third-party owned systems, and long-term power purchase contracts. We find that the effectiveness of each risk reduction option varies by region, depending on which factors drive regional PV investment uncertainty

2A)

Diesel engine emissions regulations and demands for better fuel economy are causing engine manufacturers to develop more advanced engine platforms. Multiple fuel injection events are now possible with high pressure common rail systems. The air path system can be controlled using combinations of actuators and advanced turbocharger systems. This increased flexibility dramatically increases the complexity of the control strategy and calibration efforts needed for new engine platforms. This study presents a new control structure for diesel engines using scheduling variables that are related to the cylinder conditions. This can reduce the number of calibrations needed compared to conventional techniques. A list of candidate parameters to be used as the scheduling variables is developed. Accurately quantifying the scheduling variables during engine operation is a primary requirement for the control structure to function effectively. Equations for each of the parameters are developed based on production sensors and models. The quality in predicting the parameters is derived based on the uncertainties in the models and measurements resulting in analytical uncertainty equations. These equations can be applied to any engine platform providing support for control input selection paired with the most appropriate sensing system. The uncertainty equations are applied to a 2.8 L diesel engine to show the application and benefit to quantifying the uncertainty in the control inputs.

Note:In 2nd question i don't know about the risk of power souce Diesel engines.If you want answer please send it separately.Thank you.