NG tank contribution in the integrated energy networks

Hamedi, Alireza; Seifi, Ali Reza

doi:10.1049/el.2019.1797

Cited by 1 publication

(2 citation statements)

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“…The technical and economic performance features of battery energy storage must be taken into account to reach the optimum operation of total energy network. The formulations of the battery storage model are as ( 5)-( 9) [2,29] The state of charge (SOC) battery at each time period is described as Ee(t). The border of SOC is bounded by (5) and it should be updated at each time period in (6).…”

Section: Energy System Modelingmentioning

confidence: 99%

“…However, the intermittent nature of the renewable generations will make the system operators balance the energy consumption and production with the new energy storage technologies. The combination of renewable energy generation and energy storage systems is a very promising method and they are becoming an essential component of energy supply and demand matching [1,2]. The energy systems are defined as the combination of sub-networks in which different type of energy networks such as the electrical and natural gas can interact and connect to each other through the energy carriers.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Operation of a Village Energy System Considering Renewable Resources and Battery Energy Storage

Hamedi,

Keihan Asl,

Seifi

2023

J. Electron. Electric. Eng.

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In this paper, a village energy system is coupled with the wide-area energy network based on the energy hub concept. The village is modeled as an isolated energy hub while it could interact with the energy sub-networks including the electrical, and natural gas through the market. The energy demand of village is supplied with renewable resources such as photovoltaic (PV) system and other generation such as combined heat and power (CHP) technologies. The CHP unit is modeled by the part-load performance. In addition, the battery energy storage is presented beside the PV system to damp the intermittent generation of PV and to be utilized in the high prices of the market. The optimal operation problem is solved to maximize the profit from the energy hub operator point of view. The optimization problem is solved with the teaching-learning based optimization (TLBO) method. The results show that the proper interaction of the village energy system with the upstream sub-networks is so affordable for the system operator to increase the profit, in a way that the maximum benefit of village energy system is reached to 3.6456$.

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