Design and implementation of an intelligent multi-input multi-output Sugeno fuzzy logic controller for managing energy resources in a hybrid renewable energy power system based on Arduino boards

Zangeneh, Mehdi; Aghajari, Ebrahim; Forouzanfar, Mehdi

doi:10.1007/s00500-021-06288-x

Cited by 12 publications

(4 citation statements)

References 42 publications

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“…In formula (10), SoC ref represents the reference SoC of lithium battery of the hybrid electric vehicle, SoC BAT,ch and SoC BAT,disch represent the charging and discharging efficiency of lithium battery of the hybrid electric vehicle, P FC, min represents the minimum output power of fuel cell, P FC, max represents the maximum output power of fuel cell, −P BAT and P BAT represent the range of output power of lithium battery of the hybrid electric vehicle, and all constraint boundaries are obtained from the platform of hybrid electric vehicle test of fuel cell [15,16].…”

Section: Multienergy Management Strategy Based On Improved Deep Q-lea...mentioning

confidence: 99%

Multienergy Management Strategy of Fuel Cell Hybrid Vehicle Based on Distributed Parameter Model

Liang

et al. 2022

Mathematical Problems in Engineering

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To increase the fuel efficiency of fuel cells, lengthen their useful lives, and fulfil the demands for high energy and high power during the operation of hybrid electric vehicles. This paper's goal is to thoroughly examine the distributed parameter model-based multienergy management technique of fuel cell hybrid electric vehicles. Firstly, the simplified model of a hybrid system is constructed according to the distributed parameter model, and the fuel cell model, unidirectional DC/DC converter, and battery are described in detail. The multienergy management of hybrid electric vehicles based on improved deep Q-learning is adopted, the multienergy management strategy based on deep Q-learning is designed, so as to reduce fuel consumption and improve the working efficiency of fuel cells, optimize the energy distribution of lithium batteries and fuel cells, and adopt the experience playback mechanism of summation tree structure in the process of strategy training to complete the multienergy management of hybrid electric vehicles. The strategy described in this study can successfully increase the overall power performance of fuel cell hybrid vehicles, extend the battery's service life, and increase fuel economy, according to simulation results, which has a certain practical value.

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Section: Multienergy Management Strategy Based On Improved Deep Q-lea...mentioning

confidence: 99%

Multienergy Management Strategy of Fuel Cell Hybrid Vehicle Based on Distributed Parameter Model

Liang

et al. 2022

Mathematical Problems in Engineering

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“…to attain the optimal indoor temperature set-point of zone i, where w G and w D are the weighting factors, G i function denotes the energy consumption of the A/C system in zone i, D i,n function represents the discomfort function of occupant n in zone i, S i represents the set of occupants located in zone i. It is worth noting that the proposed indicator (12) results in different balances between the energy consumption and thermal comfort with different weighting factors. To be specific,…”

Section: Improved Indoor Thermal Preference Indicatormentioning

confidence: 99%

“…Toward the A/C system control logic to minimize the difference between the actual indoor temperature and the optimal indoor temperature set‐point in a zone, a large number of methods can be well observed. Among the existing methods, fuzzy logic control 12 is effective in catching the nonlinear dynamics of the A/C system, but its applicability is limited owing to the dynamic operation conditions of the A/C system. To overcome this limitation, intensive attention has been dedicated to novel control methods, such as adaptive control 13 and reinforcement learning methods, 14 the basic idea of which consists in a direct construction of the controllers without establishing the accurate first principle model of the A/C systems.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered distributed model predictive control scheme for temperature regulation in multi‐zone air conditioning systems with improved indoor thermal preference indicator

Gao

Zhang

et al. 2023

Adaptive Control & Signal

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Driven by the increasing needs in multi-zone buildings for reducing the air conditioning (A/C) system related energy consumption and increasing the occupants' thermal comfort, an event-triggered distributed model predictive control (DMPC) scheme for building temperature regulation with improved indoor thermal preference indicator is proposed. To this end, a temperature-energy model of the A/C system in a zone which considers multiple types of heat transfer, and the system model of the multi-zone A/C system are derived first. On this basis, an improved indoor thermal preference indicator that trades off the A/C systems related energy consumption with the aggregate thermal comfort of the occupants is proposed for the multi-zone A/C system, then the optimal indoor temperature set-points for each zone are determined by using the distributed consensus algorithm. It is followed by an event-triggered DMPC scheme by adjusting the A/C systems to arrive at the optimal indoor temperature set-points for all the zones with lower communication and computation load. The performance and effectiveness of the proposed methods are demonstrated through a case study on an actual multi-zone A/C system.

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“…The conception and development of an efficient multi input-output fuzzy logic smart controller, to manage the energy flux of a sustainable hybrid power system based on renewable power sources, integrating solar panels and a wind turbine associated with storage, applied to a typical residential habitat, were presented by Derrouazin et al (2017). The conception, design, and implementation of an intelligent multi-input multi-output fuzzy logic controller for the energy management of a hybrid renewable energy system, including solar power and storage battery in laboratory dimensions, were worked on by Zangeneh et al (2022). A fuzzy framework for smart home monitoring systems (FF-SHMS) effective in energy using the Internet of Things (IoT), demand monitoring, green energy conservation, energy conservation, and microgrids was presented by Alowaidi (2022).…”

Section: Introductionmentioning

confidence: 99%

Energy efficient smart home heating system using renewable energy source with fuzzy control design

Simon,

Róbert Sánta

2023

Decis. Mak. Appl. Manag. Eng.

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This research article presents an energy- efficient smart home heating system that uses a renew-able energy source and incorporates fuzzy control design. The objective of the study is to design a heating system that optimizes energy consumption while providing a comfortable indoor temperature. The main methods used in the study include the integration of a renewable energy source, such as solar energy or geothermal energy, with a fuzzy control system that adjusts the heating power based on indoor and outdoor temperature, humidity, and occupancy. The main results of the study show that the proposed heating system can reduce energy consumption by up to 40% compared to conventional heating systems, while maintaining a comfortable indoor temperature. The fuzzy control system provides precise control of the heating power and ensures efficient use of the renewable energy source. The main conclusion of the article is that the proposed smart home heating system is a viable solution for reducing energy consumption and promoting a sustainable lifestyle, especially in areas with abundant renewable energy sources.

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Design and implementation of an intelligent multi-input multi-output Sugeno fuzzy logic controller for managing energy resources in a hybrid renewable energy power system based on Arduino boards

Cited by 12 publications

References 42 publications

Multienergy Management Strategy of Fuel Cell Hybrid Vehicle Based on Distributed Parameter Model

Multienergy Management Strategy of Fuel Cell Hybrid Vehicle Based on Distributed Parameter Model

Event‐triggered distributed model predictive control scheme for temperature regulation in multi‐zone air conditioning systems with improved indoor thermal preference indicator

Energy efficient smart home heating system using renewable energy source with fuzzy control design

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