Bidding strategy for risk-averse producers in transmission-constrained electricity markets

2015 ◽  
Author(s):  
Evaggelos G. Kardakos ◽  
Christos K. Simoglou ◽  
Stylianos I. Vagropoulos ◽  
Anastasios G. Bakirtzis
Keyword(s):  
Electricity Markets ◽  
Bidding Strategy ◽  
Risk Averse

Impacts of Emission Trading on Optimal Bidding Strategies of Generation Companies in Day-Ahead Electricity Markets

2014 ◽  
Vol 521 ◽  
pp. 476-479 ◽  
Author(s):  
Guo Zhong Liu
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Emissions Trading ◽  
Emission Trading ◽  
Distribution Functions ◽  
Bidding Strategy ◽  
Chance Constrained Programming ◽  
Optimization Approach ◽  
Generation Company ◽  
Optimal Bidding

The impacts of Emission trading on building the optimal bidding strategy for a generation company participating in a day-ahead electricity market is investigated. The CO2 emission price in an emissions trading market is evaluated by using an optimization approach similar to the well-developed probabilistic production simulation method. Then upon the assumption that the probability distribution functions of rivals bidding are known, a stochastic optimization model for building the risk-constrained optimal bidding strategy for the generation company in the framework of the chance-constrained programming is presented. Finally, a numerical example is served for demonstrating the feasibility of the developed model and method, and the optimal bidding results are compared for the two situations with and without the CO2 emissions trading.

USING EXTREME VALUE THEORY TO EVALUATE CONDITIONAL VAR FOR RISK MANAGEMENT IN ELECTRICITY MARKETS

2016 ◽  
Vol 78 (10) ◽  
Author(s):  
M. T. Askari ◽  
Z. Afzalipor ◽  
A. Amoozadeh
Keyword(s):  
At Risk ◽  
Electricity Markets ◽  
Extreme Value Theory ◽  
Value At Risk ◽  
Risk Model ◽  
Test System ◽  
Value Theory ◽  
Extreme Value ◽  
Conditional Value At Risk ◽  
Bidding Strategy

In a deregulated power market, generation companies attempt to maximize their profits and minimize their risks. This paper proposes a risk model for bidding strategy of generation companies based on EVT-CVaR method. Extreme Value Theory can overcome shortcomings of traditional methods in computing financial risk based on value-at-risk and conditional value-at-risk method. Also, generalized Pareto distribution is suggested to model tail of an unknown distribution and parameters of the GPD are estimated by likelihood moment method. Numerical results for risk assessment using the proposed approach are presented for IEEE 30-bus test system. According to the findings, this method can be used as a robust technique to calculate the risk for bidding strategy of generation companies.

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