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Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach by Achiluzzi, Eleonora; Kobikrishna, Kirushaanth; Sivabalan, Abenayan; Sabillon, Carlos; Venkatesh, Bala is a Engineering article available to read on EtoBox.
What is Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach about?
In the distribution system, customers have increasingly use renewable energy sources and battery energy storage systems (BESS), transforming traditional loads into active prosumers. Therefore, methodologies are needed to provide prosumers with tools to optimize their investments and increase business opportunities. In this paper, a stochastic mixed integer linear programming (MILP) formulation is proposed to solve for optimal sizes of prosumer assets, considering the use of a BESS and photovoltaic (PV) units. The objective is to minimize the total cost of the system, which is defined as the combination of a solar PV system investment, BESS investment, maintenance costs of assets, and the cost of electricity supplied by the grid. The developed method defines the optimal size of PV units, the power/energy capacities of the BESS, and the optimal value for initial energy stored in the BESS. Both deterministic and stochastic approaches were explored. For each approach, the proposed model was tested for three cases, providing a varying combination of the use of grid power, PV units, and BESS. The optimal values from each case were compared, showing that there is potential to achieve more
Who reads Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Achiluzzi, Eleonora; Kobikrishna, Kirushaanth; Sivabalan, Abenayan; Sabillon, Carlos; Venkatesh, Bala
- Publisher
- MDPI AG; Multidisciplinary Digital Publishing Institute (MDPI); Basel: Molecular Diversity Preservation International (MDPI), 2008- (ISSN 1996-1073)
- Published
- 2020
- Language
- EN
- Field
- Engineering (Physical Sciences)