Recently, there has been an increased level of integration of renewable energy systems in existing power grids. This had led to the need to incorporate renewables in grid system planning and operations to maximize the use of the renewable power generated. Lack of integrated models has led to waste in power produced.&nbsp; This paper proposes a mixed-integer nonlinear optimization model for hybrid renewable-generator-plus-battery systems, with the objective of maximizing long-term profit. The degradation of the battery and the cost associated with eventually replacing the battery are integrated in the model. The model is designed so as to maximize energy dispatched to the grid while not exceeding grid connection limits. The system being considered for optimization consists of a wind power generating system and a battery, though other renewable generators can be modeled. This model has been accomplished by creating a novel algorithm built using Pyomo that uses equations and inequality constraints to characterize the relationship between the renewable technology, the grid and the battery. The data for the energy generated by the wind power generating system is obtained from the National Renewable Energy Laboratory's System Advisor Model (SAM) Wind Power System module. Energy being sent to the grid was incentivized. The surplus energy was sent to the battery from where it was dispatched to the grid in times of shortage in energy production, thereby generating a battery profile.Prior studies have revealed that both high and low state of charge (SOC) of the battery is detrimental to its lifetime and results in reduced battery capacity over time. In addition, increased number of cycles of charge and discharge -- in other words, intensive use of the battery -- also causes capacity reduction. This paper models these two factors with a bilinear constraint relating capacity loss to the SOC and number of cycles completed by the battery. Finally, the loss in capacity is penalized in the objective function of the optimization model, thereby indirectly penalizing high and low SOC’s and frequent cycling.As the model becomes more complex, it becomes increasingly difficult for solvers to achieve global optimality in a reasonable time period. To overcome this difficulty, we use a rolling time horizon optimization approach.&nbsp; By incorporating battery degradation in the real-time model, the model is capable of maximizing the profits from the power dispatch to the grid while also maximizing the life of the battery. This also reduces power wastage by more carefully scheduling the usage of the power systems and battery.&nbsp;&nbsp;This paper exercises the model by assessing a number of sample generator time series profiles with a range of battery capacities. The results demonstrate that the batteries lifetime is extended in comparison to conventional models that ignore battery degradation in dispatch decisions. The efficacy of the model is tested by comparing the scheduling of power dispatch of existing power systems to the dispatch generated by the novel algorithm. It is seen that the novel algorithm extends battery lifetime while maximizing profits, thereby fulfilling the objective.

A Dispatch Optimization Model for Hybrid Renewable and Battery Systems Incorporating a Battery Degradation Model

Paper Proceedings: https://asmedigitalcollection.asme.org/ES/ES2021/volume/84881

ASME 2021 Energy Sustainability (ES2021)

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