planning and operation scheduling of pv-battery systems: a novel methodology - storage battery systems

The purpose of this paper is to develop a decision support tool for grid investment decision-making, optimization scale and operation scheduling
Connected PV/battery systems in terms of periodic weather data, electricity prices, PV/battery system costs, PV/battery specifications, desired reliability, and dynamics of other key design and operating parameters.
We review the historical development literature of photovoltaic models
Battery system size. A multi-period mixed-
Integer linear programming (MILP)
Then introduce the objective of maximizing the net present value of cash flow (
For investment analysis)
Or savings in electricity (
For Operation scheduling).
For investment decision analysis, the model is able to determine whether the investment in photovoltaic and/or battery systems is economical, if positive, it can find the best PV and/or battery systems from the combination of available options.
In addition, the model defines the optimal size of the selected PV and/or battery systems.
If feasible, the model will select a combination of one or several systems.
Within the planning scope, all of these decision variables are determined at the same time as finding the optimal operating schedule for PV and/or battery systems in each cycle.
These variables include the power flow of the gridto-load, PV-to-load, battery-to-load, battery-to-grid, grid-to-battery, PV-to-battery, PV-to-
Grid and battery status-of charge.
This decision support program enables consumers (
From small house to big house-
Industrial plant of scale)
While achieving the goal of minimizing electricity charges, the most effective electricity management strategy is implemented.