风电及其联营体参与电力市场交易策略研究综述及展望OA

The randomness of wind power output,its weak regulating capacity,and the uncertainty of market prices make it difficult for wind power to recover costs and secure reasonable returns.For example,in the electricity spot market,given that wind power output has a high coincidence rate,there is an abundance of electricity supply during periods of high wind power generation.Yet,spot market prices are low at such times,exposing wind power to significant revenue risks in spot market transactions.In the medium and long-term market,wind power output is hard to predict accurately.After signing curve contracts,there is also substantial performance risk.In this case,if wind power companies lack guidance from relevant theories and methods to formulate scientific and reasonable electricity market transaction strategies,they will face certain risks to their sustainable operations. Existing research on wind power trading strategies primarily focused on models for wind power and its aggregators in one or two market types.Studies covered combinations with flexible resources like energy storage.Some involved participation in spot markets as price takers or makers.Others focused only on mid-or long-term markets,or on both spot and ancillary service markets.Several reviews also examined coupled transactions in policy-driven markets,such as green certificate and carbon markets.However,no comprehensive review addressed transaction strategies for wind power and its aggregators across electricity markets,including spot and ancillary services.Since electricity market revenue constitutes the main income for wind power projects,and existing studies involve diverse markets,participants,and optimization methods,a systematic analysis was lacking.A thorough review was therefore necessary to clarify current research and identify future directions. To address this need,a systematic review was conducted on transaction strategies for wind power and its aggregators in electricity markets.Transaction strategies typically consist of market bidding curves defined by quantity and price.These curves allow operators to maximize overall power generation profits.Constructing such curves required building and solving a strategic optimization model.The model aimed to maximize generalized profit—considering both income and risk—subject to unit operational constraints and market rules.Modeling tools accounting for uncertainty were employed.Thus,three key factors influenced strategy formation:participating entities,market types,and methods for addressing uncertainty. Based on the above analysis,the study examined three key factors in building transaction strategy models for wind power and its aggregators.The review process first analyzed bidding mechanisms in international and domestic electricity markets to identify eligible market types and related rules.Next,due to strong interactions between market types and participants,a hierarchical framework was established,organizing the review by market type and subdividing by participating entity.Chapter 5 specifically addressed optimization models handling uncertainties in wind power and electricity prices,assessing the strengths,limitations,and suitable applications of each method.Finally,recommendations were proposed regarding strategic decision-making for market participants and improvements to market mechanisms.