Optimal Electricity Transmission Pricing in a Restructured Electricity Market

Abstract

In last two decades, electricity markets have significantly restructured in both developed and developing countries. This restructuring introduced competition both wholesale and, in some cases, in the retail segments of the electric power industry. A common element of electricity restructuring is the unbundling of generation and transmission, with the latter being opened for use by all eligible market participants under the open access regime. Transmission pricing in open access regime is one of the active area of research. In developing countries, transmission pricing is mainly addressing the issue of recovering embedded cost or past investment and optimal allocation of variable cost at different nodes over the grid. Pricing methods should capable to translate transmission cost into tariffs to enable competition, lead to economic efficiency, enable the grid owner to recover his cost and more transparent to market participants while maintaining supply security and reliability of the system. This study aims at (1) motivations for electricity transmission pricing, (2) formulating AC-DC OPF based embedded and nodal pricing (3) computing prices for IEEE 30-Bus system and real transmission network of India. Study finally concluded that proposed methodology are more suitable for developing countries to fulfill their objectives of developing wholesale electricity market.

Scheduled incremental and unscheduled interchange cost components of transmission tariff allocation: a novel approach for maintaining the grid discipline

“…S sij = P sij + jQ sij (11) subjected to the absolute MVA flow through circuit as S sij = S sij , for P sij ≥ 0 and…”

“…The evaluation of LRIC has been proposed to handle the uncertainty of load growth in [10] by the authors. AC–DC optimal powerflow‐based fixed embedded cost and optimal nodal pricing‐based variable cost is presented in [11] with transmission pricing simulation. The response of new and existing network users to pricing signals is provided by Li et al .…”

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“…Roseline et al [13] discussed a case study of Tamil Nadu, India and explained different components such as power generation, man power rationalization, renewable energy, and transmission and distribution losses. Warkad et al [14] applied MW-Mile and MVA-Mile methods to Maharashtra State Electricity Transmission Company Limited (MSETCL) network and worked out optimal cost of tariff for MSETCL system. The effect of reactive power flow caused by the wheeling transaction has been explained using the IEEE-30 bus and Indian utility-62 bus systems.…”