[Objective] In the contemporary electricity spot market

the continuous fluctuation of electricity prices has become a critical factor influencing the operational costs and overall economic viability of coal-fired power generating units. Conventional optimization models for power plant operations typically focus on thermodynamic efficiency or coal consumption rates in isolation

which makes it difficult to reflect the real-time impact of dynamic electricity price changes on the actual profitability of the unit. [Methods] To address the challenge of economic sensitivity to price volatility

this research proposes a novel operational optimization strategy for once-through cooling systems that explicitly integrates time-of-use electricity price signals. This strategy dynamically balances coal consumption cost and circulating water pump power consumption

ensuring the unit achieves maximum net revenue while meeting required heat exchange performance requirements. Using empirical data collected from a 1 000 MW coal-fired unit between July 2024 and August 2025

alongside local time-of-use electricity price curves

this study constructs a comprehensive multivariate decision-making model. This model incorporates critical variables such as unit load levels

cold source environmental characteristics

and market price fluctuations to evaluate and determine the optimal control schemes across various seasonal conditions. [Results] The research findings indicate a significant shift in optimal operational logic depending on market conditions. Specifically

during periods of price troughs

it is more economically advantageous to appropriately increase the condenser backpressure by reducing the number of active circulating water pumps or adjusting their rotational speeds. This approach prioritizes the reduction of auxiliary power consumption over marginal gains in generation efficiency

thereby enhancing the net financial return when the market value of electricity is low. Conversely

during periods of high ambient temperatures

high load demands

or peak electricity prices

the model suggests maintaining a lower backpressure to maximize the unit's power output

thereby capturing higher market returns. Seasonal empirical analysis shows that in winter

this cold-end optimization increases revenue by 5 670.13 yuan during low-price periods and 242.08 yuan during peak periods

resulting in a total daily revenue gain of 5 912.27 yuan. In summer

the optimization yields a revenue increase of 2 861.69 yuan during low-price periods and 2 226.76 yuan during peak periods

with a total daily enhancement of 5 088.46 yuan. [Conclusion] These findings validate the feasibility of collaborative cold-end optimization considering time-of-use prices within the framework of flexible power system dispatch. This study provides significant technical support for the intelligent transformation and operational optimization of cooling systems

enhancing the market competitiveness of coal-fired units in a fluctuating economic landscape.