Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system

Abstract

We develop a stochastic optimization model for scheduling a hybrid solar-battery storage system. Solar power in excess of the promise can be used to charge the battery, while power short of the promise is met by discharging the battery. We ensure reliable operations by using a joint chance constraint. Models with a few hundred scenarios are relatively tractable; for larger models, we demonstrate how a Lagrangian relaxation scheme provides improved results. To further accelerate the Lagrangian scheme, we embed the progressive hedging algorithm within the subgradient iterations of the Lagrangian relaxation. We investigate several enhancements of the progressive hedging algorithm, and find bundling of scenarios results in the best bounds. Finally, we provide a generalization for how our analysis extends to a microgrid with multiple batteries and photovoltaic generators.

Study on PID performance degradation based on passivation materials such as alumina/silicon nitride SiN crystalline silicon solar cells

“…The amorphous membrane of transparent silicon battery has the effect of weakening reflection and inactivation, so it can also be called inactivation membrane, and its configuration is related to short-distance chylic bonds [16][17]. There are basically two kinds of inactivation membranes that are more common in daily life, namely silicon nitride membrane and silicon oxide membrane [18][19].…”