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Authors
Advisor(s)
Abstract(s)
In a liberalized electricity market, participants have several types of contracts to sell or buy electrical
energy. Increasing electricity markets liquidity and, simultaneously, providing to market participants tools for
hedging against spot electricity price were the two main reasons for the appearance of those types of contracts.
However, due to the payoff nonlinearity characteristic of those contracts, deciding the optimal portfolio that best
adjusts to their necessities becomes a hard task. This paper presents an optimization model applied to optimal
contract allocation using Particle Swarm Optimization (PSO). This optimization model consists on finding the
portfolio that maximizes the electricity producer results and simultaneously allows the practice of the hedge
against the volatility of the System Marginal Price (SMP). Risk management is considered through the
consideration of a mean-variance optimization function. An example for a programming period is presented
using spot, forward and options contracts. PSO performance in such type of problems is evaluated by comparing it with the Genetic Algorithms (GA).
Description
Keywords
Particle Swarm Optimization (PSO) Electricity Markets Contracts Risk Management
Citation
Publisher
World Scientific and Engineering Academy and Society