Open AccessBi‐layer portfolio selection model for electricity retailers based on behavioural portfolio theory under quota obligation of RPS
Author(s) -
Jiang Yicheng,
Liu Shengyuan,
Yang Li,
Lin Zhenzhi,
Ding Yi,
He Chuan,
Li Jing,
Wang Kai
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1574
Subject(s) - portfolio , renewable portfolio standard , renewable energy , modern portfolio theory , electricity market , tariff , business , capital allocation line , investment (military) , electricity , microeconomics , incentive , industrial organization , environmental economics , economics , feed in tariff , finance , energy policy , engineering , politics , international trade , law , electrical engineering , political science
With the development of renewable energy market, Renewable Portfolio Standard (RPS) has become the targeted renewable energy incentive mechanism in China and it is under a government's long‐term plan that RPS overtakes feed‐in tariff gradually in recent years. Given this background, the decision‐making model of electricity retailers to accomplish the obligation under RPS is constructed as a bi‐layer portfolio selection model. In the inner‐layer, both capital allocation of the retailers to purchase various kinds of renewable energy capacity as well as RECs are optimised. In the outer‐layer, the capital investment portfolio of each risky and risk‐free strategy is determined based on the Behavioural Portfolio Theory, with different mental accounts (MAs) with different aspiration points and threshold levels built to describe the investor philosophy of retailers during the decision‐making process. The simulation results of a provincial electricity market in China demonstrate that the presented model can effectively assist electricity retailers in making their capital investment strategies under RPS with relevant market factors. In addition, the proposed model provides insights for policy makers to set key parameters involving the design of RPS by analysing behaviours of retailers, including required quota ratio and value of fines.