Simulation and design of a large thermal storage system: Real data analysis of a smart polygeneration micro grid system

Memme, Samuele; Boccalatte, Antonio; Brignone, Massimo; Delfino, Federico; Fossa, Marco

doi:10.1016/j.applthermaleng.2021.117789

Cited by 12 publications

(7 citation statements)

References 41 publications

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“…This algorithm is the result of applying the concept of immunity and its theory to the genetic algorithm. 13,14 On the premise of preserving the good characteristics of the original algorithm, it tries to selectively and purposefully use some characteristic information or knowledge in the problem to be solved to suppress the degradation in the process of optimization. 15,16 The immune algorithm can ensure the diversity of the population by using its own characteristics of generating diversity and maintaining mechanisms, overcoming the inevitable "premature" problem in the general optimization process, and can obtain the global optimal solution.…”

Section: Overall Framework Of Artificial Immune Algorithmmentioning

confidence: 99%

“…IA is a group intelligent search algorithm with an iterative process of generation and detection. This algorithm is the result of applying the concept of immunity and its theory to the genetic algorithm 13,14 . On the premise of preserving the good characteristics of the original algorithm, it tries to selectively and purposefully use some characteristic information or knowledge in the problem to be solved to suppress the degradation in the process of optimization 15,16 …”

Section: Network Security Risk Detection Of Microgrid Monitoring Syst...mentioning

confidence: 99%

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Network security risk detection method for smart microgrid monitoring system

et al. 2023

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Although the smart microgrid improves the power quality of the power system, it still has some security risks. So, this paper proposes a network security risk detection method of an intelligent microgrid monitoring system based on the artificial immune algorithm. By analyzing the structure of a smart microgrid monitoring system and introducing Policy Protection Detection Response (P2DR) dynamic network security model and ale static network security analysis method, the network security risk of the microgrid monitoring system is evaluated. The theoretical model is analyzed by the overall framework of the artificial immune algorithm, and its term definition is given. The mutation self is detected by self‐dynamic description and immune cell evolution process with the network structure brought into and the risk of the computing network facing different attack subjects is analyzed. This method has a high detection accuracy for more than 10 kinds of network attack modes, the highest detection accuracy is 98%, and the average time is only 0.8 s. Compared with other methods, this method has higher detection accuracy and faster detection speed. It is universal in various network attack modes and can detect the possible network security risks of the intelligent microgrid monitoring system and protect its safe and stable operation.

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Section: Overall Framework Of Artificial Immune Algorithmmentioning

confidence: 99%

Section: Network Security Risk Detection Of Microgrid Monitoring Syst...mentioning

confidence: 99%

Network security risk detection method for smart microgrid monitoring system

et al. 2023

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“…The variation of solar radiation over time due to weather impedes the efficient utilisation of solar energy, in which the heat demand and supply are mismatched. Thermal energy storage (TES) is a peculiar technical solution to decoupling the demand-side from the supply-side in different time scales, storing solar energy and reutilising it at other times and places [47].…”

Section: Solar Thermal Energy Storagementioning

confidence: 99%

Solar energy utilisation: Current status and roll-out potential

Taylor

et al. 2022

Applied Thermal Engineering

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“…Xie et al [13] proposed a new solution method based on the vertical and horizontal crossover algorithm that is proposed to solve the problem of economic scheduling optimization of cogeneration. In a study by Memme et al [14] and Kumar et al [15], stochastic optimization models for metered and distributed energy were developed and solved using an improved particle swarm optimization (PSO), respectively. Most of the current studies on energy management of CCHP-type microgrids only optimize the output of each part of the CCHP system and match the customer load unilaterally, without considering the two-way matching between the supply side and the customer side and without combining the demand of the customer side.…”

Section: Introductionmentioning

confidence: 99%

Integrated Energy Management of Smart Grids in Smart Cities Based on PSO Scheduling Models

Yang,

Xu,

et al. 2023

Advances in Civil Engineering

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The supporting position and role of smart grids in the construction of smart cities have not been fully explored. Based on systematizing the system architecture of smart cities, we first analyze the facilitating and constraining roles of smart grids and smart cities with each other and make a quantitative analysis of the coordination and supporting roles between them; in the smart grid environment, we propose a framework of energy management system based on particle swarm optimization (PSO) dispatching model. The algorithm optimizes the operation of dispatchable loads, electric vehicles, and energy storage systems based on outdoor temperature forecasts, renewable energy power output forecasts, day-ahead tariff signals, and customer preferences to minimize customer electricity costs. The performance of the algorithm is verified through simulation experiments, and the results show that the proposed algorithm significantly reduces electricity consumption costs by 32.54% compared to algorithms that only optimize the scheduling of loads or some components of the home energy management system.

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Simulation and design of a large thermal storage system: Real data analysis of a smart polygeneration micro grid system

Cited by 12 publications

References 41 publications

Network security risk detection method for smart microgrid monitoring system

Network security risk detection method for smart microgrid monitoring system

Solar energy utilisation: Current status and roll-out potential

Integrated Energy Management of Smart Grids in Smart Cities Based on PSO Scheduling Models

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