A Novel PV Planning Model for Power Distribution Systems Considering Carbon Emissions and Network Losses

Considering the impact of carbon emissions in distributed renewable generation (DRG) planning is essential in a carbon-constrained world. However, existing statistical methods hardly take carbon emissions into account during the planning process. Therefore, this study proposes a multi-objective optimization methodology that considers optimal location and capacity planning of photovoltaic (PV) in power distribution systems towards low-carbon sustainability. To achieve this goal, particle swarm optimization (PSO) algorithm with power flow is used in the optimization process. The multi-objective functions such as maximizing the potential carbon emission cost saving and minimizing the PV absorption rate in power distribution systems are transformed into the single objective using weighted sum method. A case study is conducted based on the IEEE 33-bus test system to illustrate the effectiveness of the proposed method and mitigating carbon footprint of power distribution systems without and with considering PV installation. The optimization results show that after installing PV in the test system, the potential carbon emission cost saving can be maximized at $373.89 in a day, while greatly reducing network losses.