Enhancing the Efficiency of Multi-Electrolyzer Clusters with Lye Mixer:Topology Design and Control Strategy

The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers.These setups present various operational modes:independent operation and multi-electrolyzer parallelization,each with distinct advantages and challenges.This study introduces an innovative configuration that incorporates a mutual lye mixer among electrolyzers,establishing a weakly coupled system that combines the advantages of two modes.This approach enables efficient heat utilization for faster hot-startup and maintains heat conservation post-lye interconnection,while preserving the option for independent operation after decoupling.A specialized thermal exchange model is developed for this topology,according to the dynamics of the lye mixer.The study further details startup procedures and proposes optimized control strategies tailored to this structural design.Waste heat from the caustic fully heats up the multiple electrolyzers connected to the lye mixing system,enabling a rapid hot start to enhance the system’s ability to track renewable energy.A control strategy is established to reduce heat loss and increase startup speed,and the optimal valve openings of the diverter valve and the manifold valve are determined.Simulation results indicate a considerable enhancement in operational efficiency,marked by an 18.28%improvement in startup speed and a 6.11%reduction in startup energy consumption inmulti-electrolyzer cluster systems,particularlywhen the systems are synchronized with photovoltaic energy sources.The findings represent a significant stride toward efficient and sustainable hydrogen production,offering a promising path for large-scale integration of renewable energy.

An Efficient Decomposition Method for Bilevel Energy Storage Arbitrage Problem

With the reduction of cost,large-capacity energy storage unit is playing an increasingly important role in modern power systems.When a merchant energy storage unit participates in the power market,its arbitrage problem can be modeled via a bilevel program.The lower-level problem simulates power market clearing and gives the nodal price,based on which the upperlevel problem maximizes the arbitrage profit of energy storage.To solve this bilevel problem,the conventional method replaces the lower level problem with its KKT optimality conditions and further performs linearization.However,because the size of the market clearing problem grows with the scale of the power system and the number of periods,the resulting MILP(mixed-integer linear program)is very challenging to solve.This paper proposes a decomposition method to address the bilevel energy storage arbitrage problem.First,the locational marginal price at the storage connection node is expressed as a piecewise constant function in the storage bidding strategy,so the market clearing problem can be omitted.Then,the storage bidding problem is formulated as a mixed-integer linear program,which contains only a few binary variables.Numeric experiments validate the proposed method is exact and highly efficient.