The co-optimization of energy and reserves has become a standard requirement in integrated markets. This is due to the inverse relationship that exists between energy and reserves. The provision of reserves generally reduces the amount of primary energy a generating unit can produce and vice versa. This suggests that these products should be procured through a simultaneous auction to ensure optimal procurement and pricing. Furthermore, forward markets dictate that this co-optimization of energy and reserves be done over a multi-period planning horizon. This dissertation addresses the problem of optimal scheduling and pricing of energy and reserves over a multi-period planning horizon using an optimal power flow formulation.
The extension of the problem from a static optimization problem to a dynamic optimization problem is presented. Price definitions for energy and reserves in terms of shadow prices emanating from the optimization algorithm are provided. It is shown that the proposed formulation of prices leads to the cascading of reserve prices and eliminates the problem of “price reversal” where lower quality reserves are priced higher than higher ii
quality reserves. Pricing conditions are also established for the downward substitution of higher quality reserves for lower quality reserves.
The proposed pricing formulations are tested on the IEEE 24 Bus Reliability Test System and on the South African power network. The simulated results show that cascading of reserve prices does occur and that prices of different types of reserves are equal when downward substitution of reserves occurs. Zonal reserve requirements result in higher energy and reserve prices, which in term result in higher procurement costs to the system operator and higher profits to market participants. Congestion on the network also results in higher procurement costs to the system operator and higher profits to market participants in the case of zonal pricing of reserves.
Dissertation (MEng)--University of Pretoria, 2013.