Due to the opening of the energy market and agreements for the reduction of pollution emissions, the use of microgrids attracts more attention in the scientific community, but the management of the distribution of electricity has new challenges. This paper considers different distributed generation systems as a main part to design a microgrid and the resources management is defined in a period through proposed dynamic economic dispatch approach. The inputs are obtained by the model predictive control algorithm considering variations of both pattern of consumption and generation systems capacity, including conventional and renewable energy sources. Furthermore, the proposed approach considers a benefits program to customers involving a demand restriction and the costs of regeneration of the pollutants produced by conventional generation systems. The dispatch strategy through a mathematical programming approach seeks to reduce to the minimum the fuel cost of conventional generators, the energy transactions, the regeneration of polluted emissions and, finally, includes the benefit in electricity demand reduction satisfying all restrictions through mathematical programming strategy. The model is implemented in LINGO 17.0 software (Lindo Systems, 1415 North Dayton Street, Chicago, IL, USA). The results exhibit the proposed approach effectiveness through a study case under different considerations.

The production of biofuels from agricultural biomass has attracted much attention from researchers in recent years. Biomass residues generated from agricultural production of corn and barley represent an essential source of raw material for the production of biofuels, and a mathematical programming-based approach can be used to establish an efficient supply chain. This paper proposes a model of mixed-integer linear programming (MILP) that seeks to minimize the total cost of the bioethanol supply chain. The proposal allows determining the optimal number and location of storage centers, biorefineries, and mixing plants, as well as the flow of biomass and bioethanol between the facilities. To show the proposed approach, we present a case study developed in the region of Tulancingo, Hidalgo, in Mexico (case study), considering the potential of biomass (corn and barley residues) in the region. The results show the costs for the production of bioethanol, transportation, and refining and total cost of the bioethanol supply chain, besides a sensitivity analysis on the costs of the bioethanol supply chain which is presented by mixing different percentages of bioethanol with fossil fuel to satisfy the demand. We conclude that the proposed approach is viable in the process of configuring the supply chain within the proposed study region.

Proportional integral (PI) control is still the most widely deployed controller in the industrial drives due to its simplicity and the fact that it is easy to understand and implement. Nevertheless, they are successes applied to systems with a complex behavior with a nonlinear representation, but a disadvantage is the procedure to find the optimal PI controller gains. The optimal values of PI parameters must be computed during the tuning process. However, traditional tuning techniques are based on model and do not provide optimal adjustment parameters for the PI controllers because the transient response could produce oscillations and a large overshoot. In this paper, six swarm intelligence-based algorithms (whale, moth-flame, flower pollination, dragonfly, cuckoo search, and modified flower pollination), are correctly conditioned and delimited to tune the PI controllers, the results are probed in a typical industry actuator. Also, a rigorous study is developed to evaluate the quality and reliability of these algorithms by a statistical analysis based on non-parametric test and post-hoc test. Finally, with the obtained results, some time simulations are carried out to corroborate that the nonlinear system performance is improved for high precision industrial applications subjected to endogenous and exogenous uncertainties in a wide range of operating conditions.

In today’s automotive industry, Lean production systems are used successfully to reduce delivery times. The current case study addresses a problem that affects an automotive company, which is the excessive delivery time of a spare part to its both national and international authorized dealers. In order to reduce the delivery time of this replacement part, the Lean Manufacturing methodology was used. For this purpose, the value stream mapping and the proposed A3 report are the tools used. With the use of these tools, activities that did not add any value are eliminated or modified; in addition, the logistical flow of the modules of the door-side trim panel delivery process is improved. As a result, added value is increased, the delivery time is reduced (for Mexico) and the number of product variants is reduced. Now, the painting process is done by the authorized dealers, and the number of pieces used for every spare part was estimated. The study demonstrates that the integration of value stream mapping administrative/productive in conjunction with the A3 report proposal allows to identify and eliminate waste in the delivery process.

The problem of economic dispatch in a micro-grid interconnected to the conventional electrical system consists of optimizing the operating cost to satisfy the different operating requirements and the demand for electrical power required by the users. In the development of this proposal, there are challenges caused by the random nature of electricity generation systems based on renewable energy sources, for an adequate operation of the micro-grid, which can be solved through systems Energy Storage System (BESS). This paper addresses the problem of optimal economic dispatch in a microgrid that includes an energy storage system based on a battery bank and interconnected to the main grid through a mathematical programming approach, considering the benefits for customers by reducing their demand of electrical power and taking into account the costs of treatment pollutants produced by conventional energy sources. The generation systems used to satisfy the energy demand of the customers within the interconnected micro-grid are: a) conventional diesel generators, b) wind generation systems, c) photovoltaic systems, d) a hydroelectric turbine, and e) a storage system based on electric batteries. The results of the effectiveness of the proposed mathematical model show that the demand for electrical power to the main grid can be reduced and customers obtain economic benefits by integrating the incentive-based demand response program into the energy management problem when environmental contingency events occur. The results show that when there are peaks in energy demand, the operating costs of the micro-grid increase by up to 380%. In the same way, when there are failures in renewable energy sources, storage systems (BESS) and diesel generators work at 100% of their capacities. The proposal is implemented in Lingo 17.0 software and simulation results show the feasibility of the proposal through the optimization of the operation of the micro-grid.

In this paper, a neuroadaptive robust trajectory tracking controller is utilized to reduce speed ripples of permanent magnet synchronous machine (PMSM) servo drive under the presence of a fracture or fissure in the rotor and external disturbances. The dynamics equations of PMSM servo drive with the presence of a fracture and unknown frictions are described in detail. Due to inherent nonlinearities in PMSM dynamic model, in addition to internal and external disturbances; a traditional PI controller with fixed parameters cannot correctly regulate the PMSM performance under these scenarios. Hence, a neuroadaptive robust controller (NRC) based on a category of on-line trained artificial neural network is used for this purpose to enhance the robustness and adaptive abilities of traditional PI controller. In this paper, the moth-flame optimization algorithm provides the optimal weight parameters of NRC and three PI controllers (off-line) for a PMSM servo drive. The performance of the NRC is evaluated in the presence of a fracture, unknown frictions, and load disturbances, likewise the result outcomes are contrasted with a traditional optimized PID controller and an optimal linear state feedback method.