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  4. Vol 5, Issue 2, 2022

Static Planning Analysis of Urban Energy Power System Based on Heuristic Algorithm

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DOI: 10.23977/jeeem.2022.050205 | Downloads: 14 | Views: 558

Author(s)

Xiangyu Hao 1

Affiliation(s)

1 State Grid Cangzhou Electric Power Supply Company, Cangzhou, Hebei, China

Corresponding Author

Xiangyu Hao

ABSTRACT

With the rapid development of cities in China, scientific management of urban energy systems has become a reality in order to ensure urban energy security, reduce energy costs, reduce environmental impact, and implement low-carbon city strategies. This paper aims to explore the static planning analysis of urban energy power system based on heuristic algorithm. Based on the analysis of the current situation of various types of power generation in the country, this paper takes the power system of Liaoning Province as the research object, and establishes the optimization objective function of the power system with the goal of the lowest total cost of power generation. First, through data collection and data calculation, the cost coefficients of the internal power generation cost, carbon emission cost, exhaust emission cost, land opportunity cost and reliability loss cost of various power generation energy sources are obtained. In this paper, several heuristic optimization algorithms are used to analyze the static design of urban power and multi-order network power systems, and the characteristics of the algorithms are summarized through the comparison and simulation of specific algorithms. Based on the characteristics of different-level classification resource allocation in multi-networks, this paper proposes a comprehensive algorithm to improve the system coordination speed and system performance.

KEYWORDS

Heuristic Algorithm, Urban Energy, Power System, Static Analysis

CITE THIS PAPER

Xiangyu Hao, Static Planning Analysis of Urban Energy Power System Based on Heuristic Algorithm. Journal of Electrotechnology, Electrical Engineering and Management (2022) Vol. 5: 33-39. DOI: http://dx.doi.org/10.23977/jeeem.2022.050205.

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