Demand Response for Flat Nonlinear MIMO Processes using Dynamic Ramping Constraints

TL;DR

This paper extends dynamic ramping constraints to complex multi-input multi-output nonlinear processes, enabling real-time scheduling with guaranteed feasibility by using a coordinate transformation and piecewise affine approximation.

Contribution

It introduces a novel coordinate transformation for flat MIMO processes and develops a mixed-integer linear formulation for dynamic ramping constraints.

Findings

Feasible operation is guaranteed with the proposed formulation.

The method effectively schedules a heated reactor-separator process.

Bridges the gap between detailed models and simplified scheduling methods.

Abstract

Volatile electricity prices make demand response (DR) attractive for processes that can modulate their production rate. However, if nonlinear dynamic processes must be scheduled simultaneously with their local multi-energy system, the resulting scheduling optimization problems often cannot be solved in real time. For single-input single-output processes, the problem can be simplified without sacrificing feasibility by dynamic ramping constraints that define a derivative of the production rate as the ramping degree of freedom. In this work, we extend dynamic ramping constraints to flat multi-input multi-output processes by a coordinate transformation that gives the true nonlinear ramping limits. Approximating these ramping limits by piecewise affine functions gives a mixed-integer linear formulation that guarantees feasible operation. As a case study, dynamic ramping constraints are derived for a heated reactor-separator process that is subsequently scheduled simultaneously with its multi-energy system. The dynamic ramping formulation bridges the gap between rigorous process models and simplified process representations for real-time scheduling.