The cost of peak power for end-users subject to a demand charge may be substantial, expecting to increase further with the vast growth of power-demanding devices. In cases where load-shifting is not a viable option for cost reduction, battery storage systems used for peak shaving purposes are emerging as a promising solution. In this paper, the economic benefits of implementing battery storage into an existing grid-connected photovoltaic system for a medium-scale swimming facility is studied. The objective is to minimize the total cost of electricity for the facility, including the cost of energy and peak power demand, while ensuring the longevity of the battery. An optimization model based on multi-integer linear programming is built, and simulated using a one-year time horizon in GAMS and Matlab. The main results reveal that installing a battery storage system is economically attractive today, with net savings on the total system cost of 0.64% yearly. The cost of peak power is reduced by 13.9%, and the savings from peak shaving operation alone is enough to compensate for the yearly cost of the battery. Moreover, the battery ensures additional revenue by performing price arbitrage operations. When simulating the system for an assumed 2030 scenario, the battery is found to be more profitable with a yearly net savings of 4.15%.
In this paper, firstly, a formulation for Multi-Period AC Optimal Power Flow is developed to incorporate intertemporal constraints and, specifically, equations representing energy storage systems. Secondly, a solution method for the resulting optimisation model is proposed based on the primal-dual interior point method and the mathematical details underlying the solution approach are explicitly and extensively elaborated. The developed solver is tested on a simple 3 bus system. Finally, the computationally efficiency is compared with similar GAMS-and MATLAB-based non-linear commercial solvers. The main contributions of our proposed method can be summarised as follows: a) Shorter computational time is observed in the test due to the merit of using analytical differentiation in the solution method rather than numerical, which is typically used by commercial solvers. b) The formulation and solution method provides the basis of an open-box flexible solver that can be extended to include other components of power systems.
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