The mathematical model is divided into two parts, namely: (1) a protection system operations model based on operator's heuristic knowledge of the protection system performance and (2) an optimization Unconstrained Binary Programming (UBP) model based on parsimonious covering theory.
So, to bring a solution in this field, a specific controlled system model based on the operation point of view is proposed.
Therefore, the equivalent model based on the operation point is stochastic; both structures and parameters of the equivalent model are random.
Also, a feature-based LCA system prototype tool which has the capabilities of processing product feature models, generating the life cycle process model based on product-to-operation feature mapping and performing LCI and impact assessment is proposed.
The optimization model compared to simulation model based on the reservoir operation rule curves.
A hybrid model consisting of a physical model and a statistical model based on historical plant operation data was proposed.
Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants.
This paper investigate the feasibility using of grey-box neural type models (GNM) for design and operation of model based Real Time Optimization (RTO) systems operating in a dynamical fashion.
The approach was to define an underlying unit-operations model based on the indirect heat-loss method, together with an efficiency risk factor (p). Process behaviour is simulated using a refined Monte Carlo (Latin Hypercube) sampling of 20 key input parameters that include coal feed and quality.
In this work, we use Spark to build a parallel processing model based on bit-vector operations to conduct bus non-on-time queries.
Moreover, for the physical model based design, changes in the operation of the process mean the original design condition may no longer be a true reflection of the desired quality.
