Abstract
For the last 7 years, the Republic of Croatia has been witnessing a sudden increase of distributed energy resources connecting to its power system. However, a significant problem is how to find the financial equilibrium which will satisfy the independent power producers on one side and the distribution system operator on the other. In this paper, the authors discuss the capital budgeting analysis of distributed generation projects with a goal of maximizing their net present values. The evaluation of net present values will be the central tool for finding the optimal position and size of distributed generation units in the network. By simultaneously minimizing active power losses the interests of distribution system operator will not be neglected in this study. The power production of distributed generation and power consumption of network loads will be modeled with characteristic average daily power curves with discrete hour intervals. The problem will be solved using genetic algorithm, and realized in Matlab programming environment.
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Notes
In general, a Company’s assets are financed by either debt or equity. WACC is the average of the costs of these sources of financing, each of which is weighted by its respective use in the given situation. WACC represents how much interest the Company has to pay for every dollar it finances.
The planner can acquire the above-mentioned measurements via the SCADA (supervisory control and data acquisition) system.
That is because a chromosome containing at least one DG project with NPV\(<\)0 , may have a total NPV sum greater than the chromosome which contains all the DG projects with NPV\(>\)0. By equaling a total NPV sum to zero, the planner marks the chromosome with at least one NPV\(<\)0 as unacceptable.
The capacity factor is the ratio of the net electricity generated, for the time considered, to the energy that could have been generated at continuous full-power operation during the same period.
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Prenc, R., Škrlec, D. & Đurović, M.Ž. The implementation of capital budgeting analysis for distributed generation allocation problems. Electr Eng 97, 225–238 (2015). https://doi.org/10.1007/s00202-015-0330-9
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DOI: https://doi.org/10.1007/s00202-015-0330-9