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 - Funding Information:
Support of National University of Sciences and Technology, Arizona State University and University of Strathclyde is acknowledged. Authors are thankful for guidance of Dr Leigh Tesfatsion, Dr Ivana Kockar, Dr Waqquas Bukhsh and Dr Muhammad Rafiq Asim. This research work was funded by the Commonwealth Scholarship Commission and USAID . Authors are grateful to anonymous reviewers for critical feedback and additional insights leading to value addition.
Funding Information:
Support of National University of Sciences and Technology, Arizona State University and University of Strathclyde is acknowledged. Authors are thankful for guidance of Dr Leigh Tesfatsion, Dr Ivana Kockar, Dr Waqquas Bukhsh and Dr Muhammad Rafiq Asim. This research work was funded by the Commonwealth Scholarship Commission and USAID. Authors are grateful to anonymous reviewers for critical feedback and additional insights leading to value addition.
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
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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 -