Technical economic analysis of PV-driven electricity and cold cogeneration systems using particle swarm optimization algorithm

Perrigot, Antoine; Périer-Muzet, Maxime; Ortéga, Pascal; Stitou, Driss

doi:10.1016/j.energy.2020.119009

Cited by 23 publications

(5 citation statements)

References 31 publications

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“…The global extremum is the individual extremum with the best fitness among all the individual extrema. The weight and connection structure of the NN corresponding to the global extremum are the current optimal solutions of the particle swarm [ 26 ].

where: pbest is the particle best position; gbest is the swarm best position; v i is the velocity vector; x i is the position vector; c 1 and c 2 are learning factors; r 1 and r 2 are two random values between 0 and 1.…”

Section: Pso-bpnn-based Performance Evaluation Model Of Knowledge Sha...mentioning

confidence: 99%

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Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN

Wang

2022

Computational Intelligence and Neuroscience

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Knowledge sharing performance is very important to evaluate the interests of industry university research alliance. Firstly, this paper puts forward the index system of knowledge sharing performance evaluation of industry university research alliance. A BP neural network (BPNN) and a PSO-improved BP neural network (PSO-BPNN) are used to establish the evaluation model, and the accuracy of the model is evaluated. The prediction accuracy is evaluated by comparing the predicted value with the target value. Through comparative analysis, it is found that the performance evaluation model based on PSO-BP neural network has high accuracy and applicability, and is an effective method of alliance knowledge sharing performance evaluation.

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Section: Pso-bpnn-based Performance Evaluation Model Of Knowledge Sha...mentioning

confidence: 99%

…”

Section: Pso-bpnn-based Performance Evaluation Model Of Knowledge Sha...mentioning

confidence: 99%

Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN

Wang

2022

Computational Intelligence and Neuroscience

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“…At the combination level of artificial neural network and intrusion detection technology, relevant European researchers tend to use artificial intelligence technology combined with encryption technology to monitor and analyze intrusion objects. The main technology includes random key management algorithm, which mainly adopts the random allocation of secret materials [ 16 , 17 ]; corresponding researchers proposed hybrid encryption algorithm based on the above random key allocation algorithm, which is mainly based on elliptic curve cryptography algorithm and advanced encryption standard algorithm for hybrid processing, so as to improve the performance of intrusion detection system [ 18 , 19 ]; relevant researchers combined with artificial intelligence algorithm proposed the intrusion detection technology of trust-based adaptive confirmation, which uses the trust algorithm of Kalman filter [ 20 ]; relevant American researchers propose refining the data model by constantly searching the corresponding relationship between data and reduce the corresponding redundant knowledge, so as to further reduce the information overload and improve the decision-making ability of the corresponding information model [ 21 , 22 ]. In the corresponding privacy protection strategy of wireless sensor networks, its main algorithms include data privacy protection scheme based on data disturbance, data privacy protection scheme based on secure multi-party technology, privacy data protection scheme based on polynomial regression, and encryption technology based on the same data state [ 23 , 24 ].…”

Section: Related Research: Research Status Of Privacy Protection and ...mentioning

confidence: 99%

Privacy Protection and Intrusion Detection System of Wireless Sensor Network Based on Artificial Neural Network

Shi¹,

Li²

2022

Computational Intelligence and Neuroscience

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With the increasing openness and development of network technology, the network based on the wireless sensor network system has increasingly become an important tool for human social life and production, but it also brings some network security problems. Among them, focus is on network privacy disclosure and foreign intrusion and the research of intrusion detection and privacy protection has increasingly become an important topic of network security. This paper deeply studies the wireless sensor network system based on neural network on the basis of traditional privacy protection and intrusion detection system. Firstly, it applies particle swarm optimization algorithm and constructs a wireless sensor network intrusion detection system based on particle swarm optimization algorithm. The system includes important modules such as data extraction, data analysis, data feedback, and auxiliary decision-making. Compared with other algorithms, particle swarm optimization algorithm does not rely on problem information. It mainly uses real numbers to solve, so the algorithm has strong universality. At the same time, its corresponding principle is simple and easy to implement and less parameters need to be adjusted. Compared with other algorithms, particle swarm optimization algorithm has fast convergence speed and little memory requirement for the computer. At the same time, this paper uses the leap of particle swarm optimization algorithm to make it easier to find the global optimal solution. At the corresponding level of wireless sensor network privacy protection, based on the original data aggregation privacy protection scheme, this paper proposes a privacy protection scheme based on polynomial regression and a user privacy protection scheme based on the same state encryption, which further improves the security of privacy protection and facilitates the management of information. To realize the integrity of user privacy information protection, this paper realizes the decryption of data based on the correlation between binary metadata and compares the corresponding decrypted data with aggregated data, so as to complete the integrity of privacy data protection. The experimental results show that the binary metadata correlation decryption method proposed in this paper and the introduction of the corresponding particle swarm optimization algorithm improve the stability of the system by about 10%, the corresponding system security by a positive proportion, and the integrity of private data by about 10%; therefore, the algorithm proposed in this paper has obvious advantages.

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“…The PV panel efficiency is noted η pv . On these latitudes, PV panels can be installed horizontally [26]. The output power of the PV panels is present in Equation (3):…”

Section: Electrical Modelingmentioning

confidence: 99%

Combined Cooling and Power Management Strategy for a Standalone House Using Hydrogen and Solar Energy

et al. 2021

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Tropical climate is characterized by hot temperatures throughout the year. In areas subject to this climate, air conditioning represents an important share of total energy consumption. In some tropical islands, there is no electric grid; in these cases, electricity is often provided by diesel generators. In this study, in order to decarbonize electricity and cooling production and to improve autonomy in a standalone application, a microgrid producing combined cooling and electrical power was proposed. The presented system was composed of photovoltaic panels, a battery, an electrolyzer, a hydrogen tank, a fuel cell, power converters, a heat pump, electrical loads, and an adsorption cooling system. Electricity production and storage were provided by photovoltaic panels and a hydrogen storage system, respectively, while cooling production and storage were achieved using a heat pump and an adsorption cooling system, respectively. The standalone application presented was a single house located in Tahiti, French Polynesia. In this paper, the system as a whole is presented. Then, the interaction between each element is described, and a model of the system is presented. Thirdly, the energy and power management required in order to meet electrical and thermal needs are presented. Then, the results of the control strategy are presented. The results showed that the adsorption cooling system provided 53% of the cooling demand. The use of the adsorption cooling system reduced the needed photovoltaic panel area, the use of the electrolyzer, and the use of the fuel cell by more than 60%, and reduced energy losses by 7% (compared to a classic heat pump) for air conditioning.

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Technical economic analysis of PV-driven electricity and cold cogeneration systems using particle swarm optimization algorithm

Cited by 23 publications

References 31 publications

Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN

Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN

Privacy Protection and Intrusion Detection System of Wireless Sensor Network Based on Artificial Neural Network

Combined Cooling and Power Management Strategy for a Standalone House Using Hydrogen and Solar Energy

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