Probabilistic game approaches for network cost allocation

In a restructured power market, the network cost is to be allocated between multiple players utilizing the system in varying capacities. Cooperative game approaches based on Shapley value and Nucleolus provide stable models for embedded cost allocation of power networks. Varying network usage necessitates the introduction of probabilistic approaches to cooperative games. This paper proposes a variety of probabilistic cooperative game approaches. These have variably been modeled based upon the probability of existence of players, the probability of existence of coalitions, and the probability of players joining a particular coalition along with their joining in a particular sequence. Application of these approaches to power networks reflects the system usage in a more justified way. Consistent and stable results qualify the application of probabilistic cooperative game approaches for cost allocation of power networks.Cooperative games, embedded cost allocation, probabilistic games, transmission pricing

IGDT based Genco's trading decision making in multimarket environment

Fossil fuel gencos are subject to influence of multiple uncertain but interactive energy and emission markets. It procures production resources from fuel and emission market and sells its generation through multiple contracts in electricity market. With increasing volatility and unpredictability in energy markets, a genco needs to make prudent decision to manage its trading in all involved markets, to guarantee minimum profit. Considering the existing market uncertainties and associated information gap, this paper proposes a robust decision making approach for gencos trading portfolio selection in all three involved markets, based on Information Gap Decision Theory (IGDT). Results from a realistic case study provides a range of decisions for a risk averse genco, appropriate to its nature, and based on the trade-off existing between robustness and targeted profit.</p

Integrated risk management model for portfolio selection in multiple markets

Risk management is a serious challenge for generating companies (gencos), because of price uncertainty in production resource procurement and selling generation outcome. Managing risk of either trading side without considering other may lead to inefficient risk management. Considering interrelated nature of market uncertainties this paper proposes integrated risk management framework for strategic trading decision making in all involved markets, in order to maximize overall expected profits. Spot and contract markets have been considered as available trading options in involved markets. Mean variance portfolio theory has been applied to solve the problem. The results from a realistic case study illustrates that decisions based on proposed approach provide better trade-off in terms of profit and risk. Revenue and cost side correlation give a new insight for diversification in portfolio selection in different trading side markets.</p