可再生能源配额考核监管与主体行为策略选择

doi:10.18402/resci.2020.12.11

Abstract

Abstract:

In order to support the healthy development of renewable energy and realize low-carbon environmental benefits, China has implemented the renewable portfolio standards policy after the coordination of multiple social interests, and strengthening the policy implementation and assessment and supervision are the guarantee for the implementation of the renewable portfolio standards. The method of evolutionary game was used to analyze the problem of quota target completion and inspection regulation among the central government, local governments, and power grid companies, and the principle of system dynamics was also used to reflect the inner game structure and its dynamic evolution mechanism of the tripartite stakeholders, whose strategic choices are discussed under different scenarios. The results show that: (1) In the scenario of punishment constraint, increasing punishment can help power grid enterprises to fulfill the dual targets of total renewable energy and non-hydropower renewable portfolio standards. But if the government lacks incentives, it will also loosen regulation. (2) Under the incentive scenario of realizing excess quota, the incentive radio is set by central government between 10% and 30%, which has a weak incentive effect on local governments to adopt a strict regulation strategy, but can have a significant incentive effect at between 33% and 47%. (3) Under the transitional scenarios, it is not the best choice for the central government to simply increase the incentive ratio. It is necessary to increase the constraint proportion of the minimum quota at the same time to realize the optimal incentive for local governments. This research may provide theoretical guidance and has practical values for the establishment and improvement of incentive assessment and supervision system of renewable portfolio standards in China.

Key words: renewable portfolio standards, assessment and supervision, incentive index, binding index, evolutionary game, strategic selection

HUANG Taozhen, SHANG Bo. Assessment and supervision of renewable portfolio standards and strategic selection of stakeholders[J].Resources Science, 2020, 42(12): 2393-2405.

Figures/Tables 16

Table 1

Tripartite game payment matrix when the central government chooses incentive assessment"

三方博弈策略（对应概率）	中央政府激励考核（ $x$ ）
三方博弈策略（对应概率）	电网企业完成双项配额任务（ $z$ ）	电网企业完成单项配额任务（ $1 - z$ ）
地方政府严格监管（ $y$ ）	$ρ (b - r g) - c d,$ $ρ r g - c g - s g q 2,$ $e 1 + e 2 + ρ e 3 + s g q 2 - c m - c t$	$δ f 1 q 1 - l - c d,$ $δ (f 2 - f 1) q 1 - c g - s g q 2,$ $e 2 + s g q 2 - δ f 2 q 1 - c m$
地方政府不严格监管（ $1 - y$ ）	$ρb - r g - c d,$ $r g - s g q 2,$ $e 1 + e 2 + ρ e 3 + s g q 2 - c m - c t$	$δ f 1 q 1 - l - c d,$ $- δ f 1 q 1 - s g q 2,$ $e 2 + s g q 2 - c m$

Table 1

Table 2

Tripartite game payment matrix when the central government chooses no incentive assessment"

三方博弈策略（对应概率）	中央政府无激励考核（ $1 - x$ ）
三方博弈策略（对应概率）	电网企业完成双项配额任务（ $z$ ）	电网企业完成单项配额任务（ $1 - z$ ）
地方政府严格监管（ $y$ ）	$δb - c d,$ $- c g - s g q 2,$ $e 1 + e 2 + s g q 2 - c m$	$δ f 1 q 1 - l - c d,$ $δ (f 2 - f 1) q 1 - c g - s g q 2,$ $e 2 + s g q 2 - δ f 2 q 1 - c m$
地方政府不严格监管（ $1 - y$ ）	$δb - c d,$ $- s g q 2,$ $e 1 + e 2 + s g q 2 - c m$	$δ f 1 q 1 - l - c d,$ $- δ f 1 q 1 - s g q 2,$ $e 2 + s g q 2 - c m$

Table 2

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Assessment and supervision of renewable portfolio standards and strategic selection of stakeholders

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