A multiparametric programming rolling horizon scheduling framework: application in a network of combined heat and power systems

We introduce a new approach for the reactive scheduling of production systems with uncertain parameters of bounded form. The proposed method follows a state-space representation for the scheduling problem, and relies on the use of a rolling horizon framework and multiparametric programming (mp) techniques. We show that by considering as uncertain parameters the set of variables that describe the state of the system at the beginning of the prediction horizon, we can effectively formulate a set of state-space mp problems that are solved just once and offline. In contrast to existing methods, the repetitive solution of a new mp after each disruptive event is avoided. The results of the parametric optimization are used in a rolling horizon basis without the need for online optimization. The proposed mp rolling horizon (mpRH) approach is applied in the scheduling of a network of combined heat and power (CHP) units

An optimization-based framework for the scheduling of operations of compressed natural gas fuelling stations: a case study of municipal bus fleet in south Kazakhstan

This work introduces an optimization-based framework for the scheduling of operations of Compressed Natural Gas (CNG) fuelling stations for municipal bus fleets. The problem under study considers technical characteristics of the bus engines as well as the distance of their routes. This allows the planning of operations of the compressor network of the CNG fuelling station in accordance with the electricity price, storage capacity and time

Optimization of single-phase multilevel inverter voltage quality using time domain problem formulation

The multilevel inverter optimal voltage quality problem is formulated in time domain in order to account for all switching harmonics. The numerical solutions establish theoretical voltage quality lower bounds for a singlephase multilevel inverter achieved for staircase modulation for entire voltage dynamic range and different voltage levels count

Optimization of single-phase multilevel inverter voltage quality using time domain problem formulation

The multilevel inverter optimal voltage quality problem is formulated in time domain in order to account for all switching harmonics. The numerical solutions establish theoretical voltage quality lower bounds for a singlephase multilevel inverter achieved for staircase modulation for entire voltage dynamic range and different voltage levels count

A rolling horizon approach for optimal management of microgrids under stochastic uncertainty

This work presents a Mixed Integer Linear Programming (MILP) approach based on a combination of a rolling horizon and stochastic programming formulation. The objective of the proposed formulation is the optimal management of the supply and demand of energy and heat in microgrids under uncertainty, in order to minimise the operational cost. Delays in the starting time of energy demands are allowed within a predefined time windows to tackle flexible demand profiles. This approach uses a scenario-based stochastic programming formulation. These scenarios consider uncertainty in the wind speed forecast, the processing time of the energy tasks and the overall heat demand, to take into account all possible scenarios related to the generation and demand of energy and heat. Nevertheless, embracing all external scenarios associated with wind speed prediction makes their consideration computationally intractable. Thus, updating input information (e.g., wind speed forecast) is required to guarantee good quality and practical solutions. Hence, the two-stage stochastic MILP formulation is introduced into a rolling horizon approach that periodically updates input information