(544e) A MULTI-Objective Optimization Approach to Optimal Sensor Location Problem in IGCC POWER Plants
A MULTI-OBJECTIVE OPTIMIZATION APPROACH TO OPTIMAL SENSOR LOCATION PROBLEM IN IGCC POWER PLANTS
In order to operate an IGCC power plant in a safe and stable manner, many input and output process parameters need to be monitored. However, due to economic and operational constraints it is infeasible to place sensors at locations pertaining to all of these parameters. Hence, it becomes important to select the most effective sensor locations which can lead us to gain maximum information about the plant conditions. Drawing on the work done by “Lee & Diwekar”, this paper attempts to broaden the realm of the optimal sensor location problem to address simultaneous optimization of multiple objective functions. In addition to “Fisher Information”, two other objective functions, viz., “thermal efficiency of the power plant” and “cost”, will be considered. Practical issues present in an IGCC power plant such as harsh physical conditions and variability in process parameters make the optimal sensor location problem an especially complicated one. Advanced simulation software and data from a set of existent sensors are used to collect information about the output parameters which do not have any sensors to gauge them yet. In order to solve this real world large scale problem, we use a novel algorithm called Better Optimization of Nonlinear Uncertain Systems (BONUS). BONUS works in probability distribution space and avoids sampling for each optimization and derivative calculations iterations.
A non-linear stochastic multi-objective problem has been solved to determine the non-dominated or Pareto set which contains different options for optimal sensor network locations that can simultaneously satisfy the three objective functions, (maximizing observability, minimizing cost and maximizing the IGCC power plant thermal efficiency).