Feasibility Approaches to Reduce the Unreliability of Gas, Nuclear, Coal, Solar and Wind Electricity Production

Methods And Case Study

We are undertaking an action research method to assist several power plants to examine clean energy models and methods to improve the reliability of electricity generation. We will apply parametric statistical techniques including descriptive analysis, distribution analysis, and simulation.

We will use several plants in the USA as source of power generation statistics (capacity and demand). Since this is a simulation, and the data is competitively sensitive, the actual power plant names will not be disclosed. Our case study operations with the daily load curve summarized in Figure 1. This was derived by the use of two beta distribution, whose general formula is: y = k(x-a)α(b-x)β (1). The parametric values for both beta distributions were determined by Evolver optimization with the result shown in Figure 1, which shows that this approach can effectively model a bimodal distribution of day time electricity demand (Nersesian, 2012).

Figure 1.

Daily load curve for a utility (megawatts)