Quantitative Indices for Improving Metro Load Curve, Using Distributed Generation

TL;DR

This paper introduces quantitative indices to evaluate how distributed generation can enhance metro load curves, addressing issues like low load factor and peak alignment with the national grid.

Contribution

It proposes a method to quantify load curve improvements using DG, based on analyzing metro consumption patterns and deriving relevant parameters.

Findings

Quantitative indices for load curve improvement are developed.

Using DG significantly enhances load curve quality.

Economic indicators like ROI are calculated from the indices.

Abstract

This paper promises the idea of using DG (Distributed Generation) to improve the Metro load curve. Public transportation systems are often based on gasoline and diesel. However, with the gradual development in usage of the Metro and monorail, a new load with heavy demand, inappropriate load curve and middle LF (Load factor) is added to the electricity grid. In addition to supply problem of this massive consumer, the Metro load curve is another problem, which has a relatively low LF. Furthermore, Metro load peak hours coincide with the peaks of national grid. Improvement of the load curve is well-known in electrical engineering literature, which depending on the type of load curve, offers general recommendations in three approaches; DSM (Demand Side Management), DS (Distributed Storage) and DG. In this paper, to achieve quantitative indices of improvement for Metro load curve using DG, firstly based on the analysis of volume and consumption pattern of the main loads in Metro, the typical load curve has been extracted. Using this curve, the result of using DG is shown by quantitative parameters which represent the significant improvement in load curve. These parameters can be used to calculate economic indicators such as initial cost and ROI (Return of Investment).