scholarly journals A Smart Adaptive Switching Module Architecture Using Fuzzy Logic for an Efficient Integration of Renewable Energy Sources. A Case Study of a RES System Located in Hulubești, Romania

2020 ◽  
Vol 12 (15) ◽  
pp. 6084
Author(s):  
Simona-Vasilica Oprea ◽  
Adela Bâra ◽  
Ștefan Preda ◽  
Osman Bulent Tor
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Power Systems ◽  
Electricity Generation ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Weather Conditions ◽  
Energy Sources ◽  
Fuzzy Logic Systems

Electricity generation from renewable energy sources (RES) has a common feature, that is, it is fluctuating, available in certain amounts and only for some periods of time. Consuming this electricity when it is available should be a primary goal to enhance operation of the RES-powered generating units which are particularly operating in microgrids. Heavily influenced by weather parameters, RES-powered systems can benefit from implementation of sensors and fuzzy logic systems to dynamically adapt electric loads to the volatility of RES. This study attempts to answer the following question: How to efficiently integrate RES to power systems by means of sustainable energy solutions that involve sensors, fuzzy logic, and categorization of loads? A Smart Adaptive Switching Module (SASM) architecture, which efficiently uses electricity generation of local available RES by gradually switching electric appliances based on weather sensors, power forecast, storage system constraints and other parameters, is proposed. It is demonstrated that, without SASM, the RES generation is supposed to be curtailed in some cases, e.g., when batteries are fully charged, even though the weather conditions are favourable. In such cases, fuzzy rules of SASM securely mitigate curtailment of RES generation by supplying high power non-traditional storage appliances. A numerical case study is performed to demonstrate effectiveness of the proposed SASM architecture for a RES system located in Hulubești (Dâmbovița), Romania.

scholarly journals An Adaptive Load Frequency Control for Power Systems with Renewable Energy Sources

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 573
Author(s):  
Mohamed Mokhtar ◽  
Mostafa I. Marei ◽  
Mariam A. Sameh ◽  
Mahmoud A. Attia
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
System Performance ◽  
Frequency Control ◽  
Renewable Energy Sources ◽  
Adaptive Controller ◽  
Load Frequency Control ◽  
Energy Sources ◽  
Load Variations

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to demonstrate the superiority of the proposed controller, the dynamic performance is compared with previous work based on an optimized controller in the third case study. Finally in the fourth case study, a sensitivity analysis is carried out through parameters variations in the nonlinear PV-thermal hybrid system. The novel application of the adaptive controller into the LFC leads to enhance the system performance under disturbance of different sources of renewable energy. Moreover, a robustness test is presented to validate the reliability of the proposed controller.

scholarly journals Unit Commitment in the Presence of Renewable Energy Sources and Energy Storage System: Case Study

2018 ◽  
Vol 12 (6) ◽  
Author(s):  
Issoufou Tahirou Halidou ◽  
Harun Or Rashid Howlader ◽  
Mohammed E. Lotfy ◽  
Atsushi Yona ◽  
Tomonobu Senjyu
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Sources

scholarly journals Fuzzy logic control of hybrid systems including renewable energy in microgrids

2020 ◽  
Vol 10 (6) ◽  
pp. 5559
Author(s):  
Omar Feddaoui ◽  
Riad Toufouti ◽  
Labed Jamel ◽  
Salima Meziane
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Power System ◽  
Hybrid Systems ◽  
Fuzzy Logic Control ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Sources ◽  
Logic Control ◽  
Wide Range

With a growing demand for more energy from subscribers, a traditional electric grid is unable to meet new challenges, in the remote areas remains the extension of the conventional electric network very hard to do make prohibitively expensive. Therefore, a new advanced generation of traditional electrical is inevitable and indispensable to move toward an efficient, economical, green, clean and self-correcting power system. The most well-known term used to define this next generation power system is Micro Grid (MG) based on renewable energy sources (RES). Since, the energy produced by RES are not constant at all times, a wide range of energy control techniques must be involved to provide a reliable power to consumers. To solve this problem in this paper we present a Fuzzy Logic Control of isolated Hybrid Systems (HRES) Including Renewable Energy in Micro-Grids to maintain a stability in voltage and frequency output especially in the standalone application. The considered HRES combine a wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on battery as a backup solution. Simulation results obtained from MATLAB/Simulink environment demonstrate the effectiveness of the proposed algorithm in decreasing the electricity bill of customer.

scholarly journals Use of an Under-Water Compressed Air Energy Storage (UWCAES) to Fully Power the Sicily Region (Italy) With Renewable Energy: A Case Study

2021 ◽  
Vol 7 ◽  
Author(s):  
Francesco Antonio Tiano ◽  
Gianfranco Rizzo
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Compressed Air ◽  
Energy Sources ◽  
Compressed Air Energy Storage ◽  
High Concentration ◽  
Renewable Sources

The high concentration of CO2 in the atmosphere and the increase in sea and land temperatures make the use of renewable energy sources increasingly urgent. To overcome the problem of non-programmability of renewable sources, this study analyzes an energy storage system consisting of under water compressed air energy storage (UWCAES). A case study for fully power the Sicily region (Italy) with renewable energy source (wind and photovoltaic) is presented. From the real annual capacity values of the renewable plants installed in Sicily, a sizing of both the energy production and the storage system and its auxiliary services is evaluated. The optimization of the operation of the system as a whole, modeled with mathematical models already validated in previous studies, is obtained through dynamic programming. The electricity consumed annually by the region, equal to 19048.4 GWh, can be entirely satisfied by renewable energy sources. A sizing of plants powered by renewable sources for a nominal power of 15, 000 MW equally divided between photovoltaic and wind power is considered. The underwater air storage system has a maximum volume of 2.1 × 108 m3, while the compression and generation units have a total nominal power of 6, 900 and 3, 100 MW, respectively. The study finally presents a sensitivity analysis for the evaluation of the effects of the variation of the power produced by renewable energy sources and of Sicily energy consumption. The results show that carbon-free feeding is possible and that all the boundary conditions on the operation of the system can be met.

An On-Line PSO-Based Fuzzy Logic Tuning Approach

2015 ◽  
pp. 1805-1830
Author(s):  
P. Babahajyani ◽  
F. Habibi ◽  
H. Bevrani
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Power Systems ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Electric Industry ◽  
Control Approach ◽  
Optimal Tuning ◽  
Proportional Integral ◽  
On Line

Modern power systems require increased intelligence and flexibility in control and optimization. This issue is becoming more significant today due to the increasing size, changing structure, emerging renewable energy sources and Microgrids, environmental constraints, and the complexity of power systems. The control units and their associated tuning methods for modern power systems surely must be intelligent (based in flexible intelligent algorithms). This chapter addresses a new intelligent approach using a combination of fuzzy logic and Particle Swarm Optimization (PSO) techniques for optimal tuning of the existing most popular Proportional-Integral (PI) or Proportional-Integral-Derivative (PID) controllers in the power electric industry. In the proposed control strategy, the PI (PID) parameters are automatically tuned using fuzzy rules, according to the on-line measurements. In order to obtain an optimal performance, the PSO technique is used to determine the membership functions' parameters. The proposed optimal tuning scheme offers many benefits for a new power system with numerous distributed generators and Renewable Energy Sources (RESs).In the developed tuning algorithm, the physical and engineering aspects have been fully considered. To demonstrate the effectiveness of the proposed control scheme, secondary frequency control problem in an islanded Microgrid (MG) system is considered a case study. The main source of power for a Microgrid is small generating units of tens of kW that are placed at the customer site. Simulation studies are performed to illustrate the capability of the proposed intelligent/optimal control approach.

An On-Line PSO-Based Fuzzy Logic Tuning Approach

2014 ◽  
pp. 589-616 ◽  
Author(s):  
P. Babahajyani ◽  
F. Habibi ◽  
H. Bevrani
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Power Systems ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Electric Industry ◽  
Control Approach ◽  
Optimal Tuning ◽  
Proportional Integral ◽  
On Line

Modern power systems require increased intelligence and flexibility in control and optimization. This issue is becoming more significant today due to the increasing size, changing structure, emerging renewable energy sources and Microgrids, environmental constraints, and the complexity of power systems. The control units and their associated tuning methods for modern power systems surely must be intelligent (based in flexible intelligent algorithms). This chapter addresses a new intelligent approach using a combination of fuzzy logic and Particle Swarm Optimization (PSO) techniques for optimal tuning of the existing most popular Proportional-Integral (PI) or Proportional-Integral-Derivative (PID) controllers in the power electric industry. In the proposed control strategy, the PI (PID) parameters are automatically tuned using fuzzy rules, according to the on-line measurements. In order to obtain an optimal performance, the PSO technique is used to determine the membership functions’ parameters. The proposed optimal tuning scheme offers many benefits for a new power system with numerous distributed generators and Renewable Energy Sources (RESs).In the developed tuning algorithm, the physical and engineering aspects have been fully considered. To demonstrate the effectiveness of the proposed control scheme, secondary frequency control problem in an islanded Microgrid (MG) system is considered a case study. The main source of power for a Microgrid is small generating units of tens of kW that are placed at the customer site. Simulation studies are performed to illustrate the capability of the proposed intelligent/optimal control approach.

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