Multiyear and multi-criteria AC Transmission Expansion Planning model considering reliability and investment costs

Abstract

-One of the major concerns in Power Systems is surely related with their reliability. Long-term expansion planning studies traditionally use the well-known deterministic "N-1" contingency criterion. However, this criterion is applied based on worst-case analyses and the obtained plan may originate over-investments. Differently, probabilistic reliability approaches can incorporate different type of uncertainties that affect power systems. In this work, a long term multi-criteria AC Transmission Expansion Planning model was developed considering two objectives -the probabilistic reliability index Expected Energy Not Supplied (EENS) and the investment cost. The Pareto-Front associated with these two objectives was obtained using Genetic Algorithms and the final solution was selected using a fuzzy decision making function. This approach was applied to the IEEE 24 Bus Test System and the results ensure its robustness and efficiency.

Transmission system planning considering solar distributed generation penetration

“…In order to estimate the EENS it is not enough to sample components out of service. In fact it is necessary to sample operation and repair times of the components in order to access the duration of each state which justifies using a chronological Monte Carlo as detailed in [8].…”

Multiyear transmission expansion planning under hydrological uncertainty

“…Subject to: Physical Constraints (3) Financial Constraints (4) Quality of service Constraints (5) In this formulation p κ is the present-worth value coefficient given by (6) and d is the discount rate.…”

“…However, it does not represent the real behavior of an AC grid and therefore can lead to solutions that corresponds to undervalued investments while also leading to serious violations of network constraints in their solutions when are checked against pure AC TEP models as reported in [4], [5]. In order to overcome these problems, the TEP problem was solved using the AC model in [6], [7].…”