Optimal allocation of distributed generation and storage systems using multi-dimensional weighted least distance optimization and water droplet algorithms

The installation of distributed generation and energy storage systems inevitably affects power system conditions such as short-circuit current, but other previous studies do not consider such an operational constraint (e.g., short-circuit current) in an optimization problem of distributed generation and energy storage systems. Therefore, the objective of this study is to optimize the type and total capacity of distributed generation and energy storage systems in terms of life cycle costs, voltage magnitude and loss variations, reliability (e.g., energy not supplied index), and protection (e.g., short-circuit current). For this purpose, this study presents a multidimensional optimization method that measures the weighted least distance in each objective function (e.g., cost, voltage, loss, reliability, and short-circuit current). This study also extends the traditional enumeration method with the water droplet algorithm. Our optimization results also show that the optimal type and capacity of a microturbine (an example of distributed generation) and a flywheel battery (an example of energy storage) can be successfully determined by the proposed approach. For example, for a residential community in Atlanta, USA with a total capacity of 2.76 MW and a radial distribution system (e.g., IEEE 34-bus test feeder), microturbines with a total capacity of 0.19 p.u. or 520 kW are optimal. If energy storage is to be installed, a combination of microturbine (0.14 p.u. or 390 kW) and flywheel (0.009 p.u. or 25 kWh) is optimal.