Abstract
In this paper we propose a new method to evaluate the effects of nationwide conservation voltage reduction (CVR) on peak-load shaving, using substation operating results management system (SOMAS) data. Its evaluation is based on a national CVR factor, which is defined as the weighted average of CVR factors associated with all transformer banks and weighting coefficients are determined by the reconstructed loads corresponding to each transformer bank. To make use of the data resulting from nationwide CVR without installing additional measuring devices, we adopt a linearized static-load model with a linearizing parameter. SOMAS data are used to evaluate the effects of nationwide CVR on peak-load shaving in the Korean power system. Evaluation results show that the national CVR factor of the Korean power system has small values in the summer season and large values in the winter season. This means that the effect of nationwide CVR on peak-load shaving in the Korean power system presents stronger benefits during winter months.
Highlights
Smart grids provide significant opportunities for utilities to control their distribution voltages effectively
We have described a new method to evaluate the effects of nationwide conservation voltage reduction (CVR) on peak-load shaving using substation operating results management system (SOMAS) data
To make use of the data resulting from nationwide CVR without installing additional measuring devices, a linearized static-load model was used to represent the transformer-bank loads
Summary
Smart grids provide significant opportunities for utilities to control their distribution voltages effectively. CVR is a well-known technique of controlling distribution voltage levels to reduce energy consumption [7,8]. Due to its complex data structure and some data errors caused by its fast communication requirements, it is difficult to use EMS data for providing accurate load modeling at a national level. In the case of SOMAS, data are sent every 2 min from every transformer bank across the country and are used to analyze load status.
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