Research on Incentive Mechanism Design and Decentralized Power Market with Consideration of Distributed Renewable Energy

doi:10.12204/j.issn.1000-7229.2021.06.004

Abstract

Abstract:

The vigorous development of renewable energy is of great significance for optimizing China’s energy structure and promoting the sustainable development of energy. In order to promote the consumption of renewable energy, it is an effective way to allow it to participate in the electricity market. However, the development of renewable energy relies on an effective incentive mechanism. The existing incentive policies for renewable energy require government control and cannot be applied for a long time when market reforms are gradually deepening. In response to the above problems, this paper constructs a decentralized power market structure suitable for renewable energy, proposes a fully market-oriented renewable energy incentive mechanism, and analyzes the decision-making behavior of power producers. The simulation results show that the proposed market structure and incentive mechanism can effectively promote the participation of renewable energy in the market clearing.

Key words: renewable energy, token incentive mechanism, electricity market, distributed optimization

CLC Number:

TM721

BAI Yuyang, ZHANG Jun, WANG Xiaohui, CHEN Siyuan, GAO Tianlu, LIU Peng. Research on Incentive Mechanism Design and Decentralized Power Market with Consideration of Distributed Renewable Energy[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(6): 29-43.

Figures/Tables 22

Fig.1 Diagram of the operation structure of distributed power market

Fig.2 Relationship between token price and quantity in the spot market

Fig.3 Relationship between token price and quantity in the forward market

Fig.4 Topology of a regional power grid system

Fig.5 Power forecast value of renewable energy units

Table 1 Cost coefficient of power generation resources in the power system

Fig.6 Iterative process diagram of market clearing

Fig.7 Load demand curve of node 5

Fig.8 MCP curve of 24 hours

Fig.9 Influence of renewable energy ratio on MCP under two scenarios

Fig.10 Iteration diagram of MCP

Table 2 Simulation parameters

Fig.11 Output diagram of renewable energy and thermal generation at 24 hours under Case 1 and Case 2 with ρ=0.05

Fig.12 Diagram of spot/forward prices and strategies of generators at 24 hours under Case 2 with ρ=0.05

Fig.13 Output diagram of renewable energy at 24 hours under Case 1, Case 2 and Case 3 with ρ=0.05

Fig.14 Output diagram of renewable energy and thermal generation at 24 hours under Case 1 and Case 2 with ρ=0.10

Fig.15 Diagram of spot/forward prices and strategies of generators at 24 hours under Case 2 with ρ=0.10

Fig.16 Output diagram of renewable energy at 24 hours under Case 1, Case 2 and Case 3 with ρ=0.10

Fig.17 Output diagram of renewable energy and thermal generation at 24 hours under Case 1 and Case 2 with ρ=0.15

Fig.18 The diagram of spot/forward prices and strategies of generators at 24 hours under Case 2 with ρ=0.15

Fig.19 Output diagram of renewable energy at 24 hours under Case 1, Case 2 and Case 3 with ρ=0.15

Table B1 Clearing energy of electricity generators in 24 hours MW·h

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