PDF(2383 KB)
A Model for Participation of Wind Hydrogen Storage Systems in Active Ancillary Services Market Trading to Improve Wind Power Availability
LI Jianlin, KANG Jingyue, WU Yiwen, JIANG Xiaoxia, LI Xiaozhu
Electric Power Construction ›› 2026, Vol. 47 ›› Issue (3) : 185-196.
PDF(2383 KB)
PDF(2383 KB)
A Model for Participation of Wind Hydrogen Storage Systems in Active Ancillary Services Market Trading to Improve Wind Power Availability
[Objective] In response to the problems of weak bidding ability and market accommodation ability of wind storage systems in the electricity market， and insufficient optimization of peak shaving ability， and in order to promote renewable energy accommodation， a day-ahead trading model for wind hydrogen storage systems to participate in the active ancillary services market is proposed. [Methods] First， the mechanism of wind power hydrogen production system is studied， and a bidding model for wind hydrogen storage systems and thermal power units in the active ancillary services market is proposed； Second， in consideration of the profit demands of both wind hydrogen storage systems and power trading institutions， a two-layer optimization model is established； Finally， through the utilization of the KKT （Karush-Kuhn-Tucker） condition and based on strong duality theory， the proposed two-layer model is transformed into a single-layer integer programming model， and numerical simulations are conducted for analysis. [Results] The results indicate that as the load increases， the trading prices of energy storage suppliers in the electricity market also increase， and the electricity supply and demand relationship in the ancillary services market exhibits a basically similar trend. The energy storage shows higher revenue when participating in the electricity market， frequency regulation ancillary service market， and reserve ancillary service market， at 544 900 yuan. Compared with energy storage only participating in the electricity market or not fully participating in the ancillary services market， the revenue is increased by 53.44%， 47.40%， and 22.59%， respectively. After the integration of the hydrogen energy coupling system， the surplus wind power can be converted into hydrogen for storage and sold for profit， achieving peak-valley arbitrage and fully accommodating wind power. In this case， energy storage suppliers considering hydrogen energy income can increase their revenue by 143 700 yuan， or 26.37%， compared to those without considering hydrogen energy income. [Conclusions] The proposed wind hydrogen storage system not only increases the revenue of operators， but also enhances the competitive advantage of the system in participating in the electricity market bidding， reducing the cost waste caused by wind power curtailment to a certain extent， and improving the level of wind power accommodation. The effectiveness of the proposed model has been verified through result analysis.
wind hydrogen storage system / active ancillary services / game theory / electricity market trading
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Isolated DC microgrids should be equipped with energy storage systems consisting of distributed energy storage units. To extend the service life of the energy storage system, the latter should keep the charge state of distributed energy storage units (DESUs) in a balanced state; however, in practice, there may be differences in the capacity of DESUs and mismatch in line resistance, which seriously affect the balancing effect of state of charge (SOC). To address this issue, this study proposes an improved sag control strategy, which enhances the discrimination of the sag coefficient to SOC variations by nesting exponential functions with power functions, thus improving the equalization effect of the SOC. Next, by defining and equalizing the power state factor, the output power of DESUs is proportionally distributed according to their capacity. To reduce the communication pressure, this study adopts a sparse communication network to convey the required information of each DESUs, i.e., the global average value is estimated by applying the dynamic consistency algorithm. Finally, a simulation model built on MATLAB/Simulink verifies the effectiveness of the proposed strategy. |
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