The penetration of renewable energy sources, particularly wind energy, into power systems has been rapidly increasing in recent years. This type of energy sources is relatively variable and unpredictable. Wind could, for example, be available at low-load periods and it may not be committed to supply power at peak-load hours, which results in a mismatch between generation and load. One of the actions that can be taken to support wind integration is the use of Energy Storage Systems (ESSs). In this paper, we formulate an AC Optimal Power Flow (OPF) problem with Battery Energy Storages (BESs) and then perform tests on IEEE 14-bus case study with different locations and numbers of BESs to discuss impacts of BES location on system operation. NOMENCLATURE 0 , 1 , 2 Cost coefficients of generating units at bus i , ℎ Cost coefficients for charging and discharging power of BES at bus j ℎ, Real charging power of BES at bus i in hour t , Real discharging power of BES at bus i in hour t ℎ, Charging efficiency of BES at bus i , Discharging efficiency of BES at bus i Energy of BES at bus i in hour t −1 Energy of BES at bus i in hour t-1 , Real generation power at bus i in hour t , Load real power at bus i in hour t , Reactive generation power at bus i in hour t ,
The penetration of renewable energy sources, particularly wind energy, into power systems has been rapidly increasing in recent years. However, the integration of wind power has posed many challenges for power system operation. For instance, this type of energy source is relatively variable and unpredictable. The installation of this renewable source might require the grid to transmit power at full capacity and some transmission lines could become congested. As a result, in some operating conditions, wind power could be curtailed, which will drive up costs for system operators. One of the actions that can be taken to support the integration of the wind is using energy storage systems. In this paper, a multiperiod ac optimal power flow problem with battery energy storages (BESs) is formulated and sets of candidate buses for BES installation are identified based on an economic criterion. Tests are carried out on IEEE 14-bus and IEEE 118-bus systems to assess the robustness of storage location on system operation
Global optimal solution to microgrid operational planning problem can be obtained by using a Modified Optimal Dispatch Strategy (MODS) which combines Load Following Dispatch Strategy (LFDS) and Cycle Charging Dispatch Strategy (CCDS). Most of the dispatching strategies formulated in microgrid operational planning problem may lead to solutions which are not necessarily global optimal. In this work, microgrid operational planning problem is formulated as Mixed-Integer Linear Programming (MILP) model which includes MODS, LFDS and CCDS.
The model includes all constraints for Diesel Generators (DGs), Storage Battery (SB) bank and reserve requirements. Contrary to the simulation-based approach found in many studies, we adopt mathematical optimization approach and implement the model in General Algebraic Modelling System (GAMS). The model is applied to plan day-ahead operation of a small microgrid in SouthSudan. Optimization is performed by using CPLEX 12 solver. MODS is found to give optimal operation plan which has minimum daily operation cost as compared to LFDS and CCDS. This model can be used to plan day-ahead operation of any hybrid PV-Wind-Diesel-Storage microgrid, enabling the operator to consider system reliability by specifying reserve requirements.
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