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Placement and sizing optimization for PV-battery-diesel hybrid systems

机译:光伏-电池-柴油混合动力系统的布局和尺寸优化

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This paper proposes a new method to determine the placement and sizing of diesel generators (DGs), photovoltaic solar panels (PV) and batteries for off-grid systems. In this work, our objective is to reduce the total system cost while fulfilling the load demand and mantaining the grid power quality, among other constraints. This is achieved by employing two particle swarm optimization (PSO) algorithms, the first for placement and sizing of the devices and the second for their scheduling. Three case studies - only DGs, DGs + PV and DGs + PV + batteries systems - based on the energy requirements of an Indonesian island are presented. In addition, real solar irradiance and temperature data are applied together with a residential load profile. The results reveal that a system which relies only on DGs is not able to keep the values of grid voltage within the tolerable range (from 0.95 p.u. to 1.05 p.u.) and a total cost of 5.8×106 USD is required. The DGs + PV system demands a lower cost, 5.2×106 USD. Nevertheless, the grid voltage reaches values lower to 0.95 p.u. for certain nodes during night time as the PV are not able to provide local power. Finally, the DGs + PV + batteries system requires the lowest cost, 4.3×106 USD, and is able to keep the values of the grid voltage within the desired range as now batteries can provide local power at night time.
机译:本文提出了一种新方法来确定离网系统的柴油发电机(DGs),光伏太阳能电池板(PV)和电池的位置和尺寸。在这项工作中,我们的目标是在满足负载需求和保持电网电能质量的同时,降低总系统成本。这可以通过使用两种粒子群优化(PSO)算法来实现,第一种用于设备的放置和大小调整,第二种用于设备调度。根据印度尼西亚岛屿的能源需求,提出了三个案例研究-仅是DGs,DGs + PV和DGs + PV +电池系统。此外,还将实际的太阳辐照度和温度数据与住宅负载曲线一起应用。结果表明,仅依靠DG的系统无法将电网电压值保持在可承受的范围内(从0.95 p.u.到1.05 p.u.),并且总成本为5.8×106 USD。 DGs + PV系统要求的成本较低,为5.2×106美元。然而,电网电压达到低于0.95 p.u的值。对于某些节点,由于PV无法提供本地电源,因此无法在夜间使用。最后,DGs + PV +电池系统要求的最低成本为4.3×106美元,并且由于现在电池可以在夜间提供本地电源,因此能够将电网电压值保持在所需范围内。

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