Matchmaking model for bilateral trading decisions of load serving entity

Abstract

Matchmaking and bilateral negotiations are two distinct phases of practical market participants’ decision making for bilateral transactions. Agent-based models are naturally suitable for electricity markets in general and bilateral transactions in particular. This paper's contribution includes development of a novel matchmaking model that generates forward contracting power and utility curves. The matchmaking model enables a load serving entity agent to undertake its own matchmaking, to find optimal trading allocations over a range of prices, before engaging in bilateral negotiations with generation company agents. Open-source agent-based simulation platform allows combined simulation of bilateral transactions and day-ahead auction. In this research paper, matchmaking is achieved by direct-search without any organized bulletin board, broker, or matchmaker. Instead of random matchmaking, portfolio optimization based matchmaking systematically explores available electricity trading options throughout the market: local and non-local bilateral trades as well as day-ahead auctions. The matchmaking algorithm is unique because it scans all trading options over the entire range of negotiable prices. Depending on private profit-seeking goals, risk-aversion preferences and market price statistics, each load serving entity agent individually finds its matchmaking results. A set of case studies demonstrates how matchmaking model depends on transmission rights and performs for different risk aversion factors.