Abstract
Line congestion margin is the available line capacity before the line becomes fully loaded. It is a quantity to measure the transmission lines security level. Placing of large scale distributed generation (DGs) units can be a key technique to alleviate line congestion, hence enhance the transmission line congestion margin, and grid security levels. However, the influence of DG integration on line congestion margin is effective at locations where transmission lines operate near to their maximum capacity. In addition, determining the required penetration level of DG (DG size) is crucial for maximizing the DG system support benefits in transmission system. A two stage approach is presented in this paper for optimal integration of large-scale wind DG for improving line congestion risk based on the congestion margin level. In stage one, a probabilistic approach is developed to predict lines with the highest probability to be congested considering the uncertainty of the line congestion margin. Once lines with a highest risk to be congested are determined at the end of the first stage, the result from stage one is employed to place DG at the node bus to which the predicted most congested line is delivering power. A Mixed Integer Linear Programing (MILP) optimization model is developed in the second stage to determine the optimal DG penetration level (DG size) for improving transmission line congestion margin considering transmission line investment deferral.
Highlights
With the increased growth in power demand, more centralized power generation capacities are built which leads to more dispatched power to flow across the transmission lines that might exceed the thermal limits of those lines, which is the primary cause of congestion in transmission lines [1]
STAGE I: CANDIDATE LINE SELECTION FOR DG ALLOCATION The proposed forecasting model is implemented considering the uncertainty of the transmission lines congestion margin
The proposed forecasting method of transmission line congestion margin is implemented based on 30 generated loading scenarios
Summary
With the increased growth in power demand, more centralized power generation capacities are built which leads to more dispatched power to flow across the transmission lines that might exceed the thermal limits of those lines, which is the primary cause of congestion in transmission lines [1]. Due to challenges associated with grid modernization aspects, transmission lines upgrades, as well as concerns brought by large penetration of large-scale renewable sources, mitigating the risk of cascading line outage and achieving optimal integration of large-scale wind generation are another drives of this work. The proposed approach in [29] adopted a probabilistic load flow along with a Generic Algorithm to place and size DGs considering transmission congestion relief. The novel contributions of this work are: 1) In terms of the line contingency analysis method proposed in stage I for determining the candidate line for DG allocation, this work is distinguished from existing research [5]–[15] as it is the first work that develops the significant correlation between the line congestion margin and its security risk probability using survival probability distribution function (SDF).
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