دانلود رایگان مقاله انگلیسی آگاهی از شرایط مبتنی بر کیو - تصمیم گیری در مذاکرات قراردادهای انرژی - الزویر 2019

ABSTRACT

Automated negotiation plays a crucial role in the decision support for bilateral energy transactions. In fact, an adequate analysis of past actions of opposing negotiators can improve the decision-making process of market players, allowing them to choose the most appropriate parties to negotiate with in order to increase their outcomes. This paper proposes a new model to estimate the expected prices that can be achieved in bilateral contracts under a specific context, enabling adequate risk management in the negotiation process. The proposed approach is based on an adaptation of the Q-Learning reinforcement learning algorithm to choose the best scenario (set of forecast contract prices) from a set of possible scenarios that are determined using several forecasting and estimation methods. The learning process assesses the probability of occurrence of each scenario, by comparing each expected scenario with the real scenario. The final chosen scenario is the one that presents the higher expected utility value. Besides, the learning method can determine which is the best scenario for each context, since the behaviour of players can change according to the negotiation environment. Consequently, these conditions influence the final contract price of negotiations. This approach allows the supported player to be prepared for the negotiation scenario that is the most probable to represent a reliable approximation of the actual negotiation environment.

Conclusions

The EM restructuring and the growth in penetration of distributed energy resources, introduced the need of a better preparation, by the part of the participating players in this dynamic environment, which trade constantly in different situations. Currently, automated negotiations are an active area of research within the field of computing, particularly with the development of artificial intelligence. However, in EM field there is not significant works to support automated negotiation decisions, as previously mentioned in the introductory section, especially those regarding the analysis of previous information from competitor players, and in particular regarding the pre-negotiation stage of negotiations. This paper proposes a model, integrated into the DECON system, to provide decision support for the pre-negotiation step of bilateral contracts in the electricity market. In summary, the pre-negotiation is a stage that has great importance because it performs all the preparation and planning of actual negotiation. This process aims to identify the ideal negotiators that supported player could trade with to obtain the greatest possible benefit.