Optimal Time-of-use Pricing For Solar Power Integrated Distribution Network Considering Random And Fuzzy Environment

Yang, Xuan; Sun, Kaiqi; Song, Chunyan; Zhaoming, Zheng; Gu, Yong; Zhang, Luliang; Chen, Jiajia

doi:10.1109/acpee51499.2021.9436942

Cited by 1 publication

(1 citation statement)

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“…The authors in [17] used particle swarm optimization algorithm with constraints to solve the optimized equipment capacity and operating parameters. The authors in [18] optimized time-of-day tariffs based on Logistic function fuzzy response mechanism to guide users to shift loads reasonably, which reduces the operating costs of the two main stakeholders, users and distribution grids. The traditional CCHP-type system consumes more primary energy, which is not conducive to environmental protection and sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimal configuration of CCHP system containing hybrid electric-hydrogen energy storage system

Ye,

Dong,

Yang

et al. 2024

Preprint

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Hydrogen energy storage technology, characterized by zero pollution, high efficiency and abundant sources, is an important means for the efficient utilization of solar energy. In the context of reducing energy consumption and the vigorous development of hydrogen energy storage technology, a multi-objective optimization configuration model with economy, energy consumption index and carbon emission index is proposed, which takes into account the working characteristics of the hydrogen energy storage system, and the exothermic heat release from the electrolysis tanks and fuel cells when they are working to provide the loads with an additional heat source of the CCHP system, to reduce energy consumption and carbon emission. Finally, taking a park as an example, a decomposition-based multi-objective optimization algorithm is used to solve the model so as to obtain a series of feasible alternatives, and at the same time a two-way projection method based on interval intuitionistic fuzzy information is used for decision-making to obtain the optimal solution, which verifies the feasibility of the system proposed in this paper.

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Section: Introductionmentioning

confidence: 99%