The Study On Mechanism Improvement And Transaction Optimization Model Of Peak-regulation Ancillary Service Of Wind Power For Northeast Power Grid

Depth implementation of energy-saving policies promotes the rapid increase of renewable energy generation capacity, taking wind power as the representative, especially the introduction of the "Renewable Energy Law" in 2005, until 2014, wind power capacity increases from 1260MW to 114609MW. In 2009, China became the fastest growing country in wind power development. In 2015, China’s new wind power installed capacity occupies the first place, accounts for 28.4 percent of the world’s newly installed capacity. But the opposite with its trend is that China’s wind power utilization is gradually declining, especially the Northeast China. During the long heating months, in order to meet the heating needs, cogeneration units must be used, the declining of thermal power peaking capacity greatly is a major challenge for the promotion of wind power utilization for Northeast Power Grid. With the rapid development of China’s wind power, strict planning system has become an important factor in increasing the amount of abandoned wind. How to adjust the existing wind power mechanism, introducing different methods and policies, establishing and improving wind power peaking mechanism, plays an important role for Northeast Power Grid. This paper researches thermal power depth peaking-regulation compensation mechanism and path optimization from improving existing peaking standards, establishing wind and thermal power generation rights trading, and learning from two-part price pilot, the specific contents and conclusions are shown as following:(1) Describes the status of peak-regulation ancillary services market of Northeast Power Grid, proposes its background significance, summarizing ancillary services status of Australia, USA, New England, Northern Europe and six regions of China-Northeast, Northwest, North China, central China, and summarizes from foreign and domestic research status of wind power peaking compensation from mechanism designing, technological innovation and policy-making, which provides a realistic basis for researching on perfecting wind power peaking ancillary services mechanism of Northeast Power Grid.(2) Eestablishes peaking optimization model for existing peaking service compensation mechanism of Northeast Power Grid. Firstly, it introduces the status, problems and improved ways of peaking ancillary service market of Northeast Power Grid. Then, it introduces K-measn cluster analysis method, selects thermal power peaking standard clustering index, establishes thermal power peaking ancillary service compensation model. Finally, taking Northeast Power Grid as example, case study shows that the proposed model can be used to set power basic peaking rate for Northeast Power Grid wind, to set the range of peaking rate according to unit capacity.(3)Proposes thermal power peaking ancillary service cost estimation model for Northeast Power Grid. Firstly, it analyzes the power generation performance impact of wind power on thermal power, including the impact on thermal power output, start and stop times and coal consumption. Then, it establishes dispatching optimization model of thermal power unit involved in wind power peaking-regulation, including wind power output scene simulation method, thermal peaking-regulation dispatching optimization model and algorithm of dispatching model. Finally, taking Liaoning power grid as example, it sets four schemes-benchmark abandoned wind, medium abandoned wind, low abandoned wind and zero abandoned wind, estimates peaking ancillary services costs of thermal power involved in wind power for Liaoning Power Grid.(4) Builds peaking-regulation compensation optimization model based on power generation rights trading for Northeast Power Grid. First, it introduces power generation trading mechanism from basic contents and features, trading ways and organization, dealmaking and settlement. Then, taking wind power that intending to abandon as generation right, it introduces power generation rights trading to establish thermal power peaking-regulation benefit optimization model. Finally, it introduces cooperative game theory to build thermal power peaking compensation model, results show power generation rights transaction can share part of wind power excess returns to thermal power units. Meanwhile, Sharply-value method can redistribute wind power grid-connected excess returns based on the contribution of each participating body, which helps to balance basic earnings of each market players and promote the development of wind power peaking ancillary services market.(5) Establishes peaking-regulation compensation model based on two-part price for Northeast Power Grid. First, taking perfectly competitive market as background, it introduces the basic contents of perfectly competitive market, MCP price mechanism and two-part price. Then, it builds Thermal power peaking-regulation cost estimation model under perfect power market. Finally, it establishes thermal power peaking-regulation compensation mechanism based on two-part price. The results show two-part price can be used to guide peaking auxiliary compensation of Northeast Power Grid, it provides electricity price gains for renewable energy by setting electricity price, which helps activate wind power peaking auxiliary market space, balance interest demand of each participators.(6) Proposes inter-provincial peaking-regulation resources trading mechanism and improvement way for Northeast Power Grid.Research on inter-provincial power trading mechanisms of promoting the large-scale use of wind power for Northeast Power Grid, which mainly includes five contents-foreign inter-province power trade, the improved ways of inter-province peaking-regulation ancillary services trading and the policy opinions of inter-province peaking-regulation trading mechanism. In order to establish inter-provincial peaking trading mechanism, the introduction of power generation right transaction actives market, promotes power inter-provincial trading. It establishes power trade pricing mechanism taking environment as the guide, increases the supervision of power trading information disclosure, and increases the enthusiasm of wind power consumptive through benchmarking.