Aparna Viswanath

Transmission expansion planning using benders decomposition and local branching

This paper studies the application of an accelerated Benders decomposition algorithm using local branching on a transmission expansion planning (TEP) problem. TEP analyses the trade-off between investment cost of adding network capacity and load curtailment cost of existing network capacity. The problem is formulated as a mixed (0-1) programming problem which is tedious to solve through conventional Benders decomposition. Local branching is used to accelerate this algorithm by dividing the feasible region of the problem into some smaller sub-regions and then using a generic solver to find the best solution in each of these sub-regions. By strengthening lower and upper bounds at earlier stages of the decomposition algorithm, local branching helps reduce number of Benders iterations to solve the TEP problem. The efficacy of this technique is demonstrated by comparing with classical Benders decomposition when applied to a 46-bus power transmission network.

Transmission expansion for profit maximization of generators in a decentralised market structure

This paper presents a transmission expansion formulation that maximizes the profits of the generators in a decentralized market structure. Transmission expansion of congested lines increases the dispatch by the generators and hence the generator surplus. The generators profit is the difference in surplus and the transmission congestion charges. Previous work on profit maximization was a simple quadratic formulation as the transmission charges were taken as fixed investment costs. In this paper, transmission congestion charges are based on the difference in spot market locational marginal prices. To ensure that transmission merchants always profits from expansion, the transmission congestion charges are modeled as several blocks of congestion prices and transmission capacities. The profitable transmission expansion for generators is thus formulated as a mixed integer (0–1) quadratic programming problem. Examples are provided to explain the method.

Renewable energy source emulator

Small scale solar and wind turbines are finding increased application in stand-alone, grid-connected and micro grid scenarios. New controllers for these devices are continually being developed. This paper documents the design and development of a low cost circuit to emulate the electrical characteristics of both photovoltaic arrays and wind turbines. The emulator circuit is intended as a tool to aid in the development of new wind turbine and photovoltaic controllers. The emulator consists of a DC / DC converter controlled by a microprocessor. A separate Maximum Power Point Tracking (MPPT) module is also described.