DEVELOPMENT OF A MONTE CARLO-BASED ECONOMIC OPTIMIZATION SCHEME FOR NUCLEAR HYBRID ENERGY SYSTEM POWER DISPATCH

摘要

The concept of Nuclear-Renewable Hybrid Energy Systems (N-R HES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. In the present test-problem configuration, the N-R HES unit is composed of three electrical power-generating components, i.e. the Balance of Plant (BOP), the Secondary Energy Source (SES), and the Energy Storage (ES), and the Industrial Process (IP), which is devoted to hydrogen generation. The general problem addressed is finding the optimum economical dispatch (ED), i.e. the power outputs of each one of unit components (BOP, SES, ES) and the IP hydrogen production level that maximizes the unit profit by simultaneously meeting individual component constraints. Because of the need of modeling and simulating the different involved dynamics, the ensuing optimization problem is characterized by a very large number of solution variables. To ease the computational burden and to improve the path to a converged solution, a suitable Monte Carlo-based optimization algorithm which provides an initial guess for the optimal N-R HES power dispatch was developed and tested. A set of stochastic power scenarios for each one of the N-R HES unit components is sampled, and then for each one of them the corresponding value of a suitably defined cost function is evaluated. Once a sufficient number of power histories was simulated, the configuration ensuring the highest profit is selected as the optimal one. The component physical dynamics are represented through suitable ramp constraints, which considerably simplify the numerical solving. Finally, the initial results were presented.