Predictive control of an integrated PV-diesel water and power supply system using an artificial neural network

Al-Alawi, Ali; Al-Alawi, S.M.; Islam, Syed

doi:10.1016/j.renene.2006.05.003

Cited by 101 publications

(38 citation statements)

References 10 publications

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“…The detection of patterns and the conversion of these patterns into knowledge and generic rules, the neuralfuzzy algorithm can assist in the risk-of-failure analysis and in the preventive maintenance of water distribution (Christodoulou and Deligianni 2010). In Al-Alawi et al (2007) research, an artificial neural network (ANN) based model is developed for the optimum operation of an integrated hybrid renewable energy based water and power supply system (IRWPSS), demonstrating that an ANN can be used with high degree of confidence to predict the control strategies.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

ANN for Hybrid Energy System Evaluation: Methodology and WSS Case Study

Gonçalves

Costa

Ramos

2011

Water Resour Manage

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Water Supply Systems (WSS) are large consumers of energy mainly used in pumping stations and treatment plants. Therefore, the improvement of energy efficiency is a major priority for water utilities. The current research work presents a new methodology and a computational algorithm based on renewable energy concepts, hydraulic system behaviour, pressure control and neural networks for the determination of the best hybrid energy configuration to be applied in a typical water supply system. The Artificial Neural Network (ANN) created to determine the best hybrid system uses scenarios with only grid supply, grid combined with hydro turbine, with wind turbine and mutual solutions with hydro and wind turbine. The ANN is trained based on values obtained from a configuration and economical simulator model (CES), as well as from a hydraulic and power simulator model (HPS). The results obtained show this ANN advanced computational model is useful for decision support solutions in the plan of sustainable hybrid energy systems that can be applied in water supply systems or other existent hydro systems allowing the improvement of the global energy efficiency. A real case study is analysed to determine the best sustainable hybrid energy solution in a small WSS of Portugal.

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Section: Artificial Neural Networkmentioning

confidence: 99%

ANN for Hybrid Energy System Evaluation: Methodology and WSS Case Study

Gonçalves

Costa

Ramos

2011

Water Resour Manage

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“…As indicated in Fig. 3, the effects of the synapses are represented by connection weights that modulate the effect of the associated input signals, and the nonlinear characteristic exhibited by neurons is represented by a transfer function [9]. The neuron impulse is then computed as the weighted sum of the input signals, transformed by the transfer function.…”

Section: B Artificial Neural Networkmentioning

confidence: 99%

Artificial intelligence techniques for controlling spacecraft power system

El-Madany¹,

Fahmy²,

El-Rahman³

et al. 2011

REPQJ

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Abstract. Advancements in the field of artificial intelligence (AI) made during this decade have forever changed the way we look at automating spacecraft subsystems including the electrical power system. AI have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. In this paper, a mathematical modeling and MATLAB-SIMULINK model for the different components of the spacecraft power system is presented. Also, a control system, which includes either the Neural Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is developed for achieving the coordination between the components of spacecraft power system as well as control the energy flows. The performance of the spacecraft power system is evaluated by comparing two control systems using the NNC and the FLC.

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“…However, diesel generators cause serious impacts on the environment as every liter of diesel releases about three kilograms of CO 2 [1]. Furthermore, diesel is expensive because transportation to remote areas adds extra cost.…”

Section: Introductionmentioning

confidence: 99%

A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization

et al. 2017

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A hybrid power system uses many wind turbine generators (WTG) and solar photovoltaics (PV) in isolated small areas. However, the output power of these renewable sources is not constant and can diverge quickly, which has a serious effect on system frequency and the continuity of demand supply. In order to solve this problem, this paper presents a new frequency control scheme for a hybrid power system to ensure supplying a high-quality power in isolated areas. The proposed power system consists of a WTG, PV, aqua-electrolyzer (AE), fuel cell (FC), battery energy storage system (BESS), flywheel (FW) and diesel engine generator (DEG). Furthermore, plug-in hybrid electric vehicles (EVs) are implemented at the customer side. A full-order observer is utilized to estimate the supply error. Then, the estimated supply error is considered in a frequency domain. The high-frequency component is reduced by BESS and FW; while the low-frequency component of supply error is mitigated using FC, EV and DEG. Two PI controllers are implemented in the proposed system to control the system frequency and reduce the supply error. The epsilon multi-objective genetic algorithm (ε-MOGA) is applied to optimize the controllers' parameters. The performance of the proposed control scheme is compared with that of recent well-established techniques, such as a PID controller tuned by the quasi-oppositional harmony search algorithm (QOHSA). The effectiveness and robustness of the hybrid power system are investigated under various operating conditions.

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Predictive control of an integrated PV-diesel water and power supply system using an artificial neural network

Cited by 101 publications

References 10 publications

ANN for Hybrid Energy System Evaluation: Methodology and WSS Case Study

ANN for Hybrid Energy System Evaluation: Methodology and WSS Case Study

Artificial intelligence techniques for controlling spacecraft power system

A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization

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