PROJECT TITLE :
Real-Time Energy Storage Management With Renewable Integration: Finite-Time Horizon Approach
We have a tendency to contemplate the planning of cost-effective management of energy storage with renewable integration for load supply. We take a finite time horizon approach and formulate the control optimization downside geared toward minimizing the system price over a fixed time amount. Recognizing the unpredictable and nonstationary stochastic nature of system dynamics, we have a tendency to assume unknown arbitrary dynamics of renewable generation, load, and electricity pricing in formulating our drawback. Furthermore, we have a tendency to incorporate detailed battery operation value into the system cost. Completely different from the infinite time horizon problems in existing works, the coupling of control choices over time, thanks to finite battery capacity, is a lot of challenging to manage. We have a tendency to develop a special technique to tackle the technical challenges in solving the problem. Through downside modification and transformation, we are ready to use Lyapunov optimization to style a real-time management algorithm that relies solely on the present system dynamics. The proposed control resolution encompasses a closed-form expression and so is simple to implement. Through analysis, the proposed algorithm is shown to own a bounded performance gap to the optimal noncausal $T$-slot lookahead control policy. Simulation studies show the effectiveness of our proposed algorithm as compared with 2 alternative real-time and noncausal algorithms.
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