TY - JOUR
T1 - Matchmaking model for bilateral trading decisions of load serving entity
AU - Imran, Kashif
AU - Ullah, Kafait
AU - Khattak, Abraiz
AU - Zhang, Jiangfeng
AU - Pal, Anamitra
AU - Rafique, Muhammad Nauman
AU - Baig, Sherjeel Mahmood
N1 - Publisher Copyright:
© 2020
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - Bilateral negotiations
KW - Day-ahead markets
KW - Direct-search bilateral trade
KW - Matchmaking
KW - Portfolio optimization
UR - http://www.scopus.com/inward/record.url?scp=85080038468&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85080038468&partnerID=8YFLogxK
U2 - 10.1016/j.epsr.2020.106281
DO - 10.1016/j.epsr.2020.106281
M3 - Article
AN - SCOPUS:85080038468
SN - 0378-7796
VL - 183
JO - Electric Power Systems Research
JF - Electric Power Systems Research
M1 - 106281
ER -