Abstract: With the proposal of the dual carbon target, innovation in low-carbon technologies such as distributed power generation has been accelerated. Aiming at the problems of high total cost and long computation time in the selection and capacity determination of distributed power sources, a distributed power source selection and capacity determination model is established with the optimization objective of minimizing total cost(distributed power investment, distributed power operation and maintenance, active network loss, power purchase, government subsidies, and environmental benefits, etc.). The model is solved using the whale algorithm optimized from three aspects(weight and convergence factor optimization, population information guidance strategy optimization, and golden sine strategy optimization) with constraints of power flow, node voltage, branch current, DG installation capacity, and node installation capacity. The superiority of the proposed method is verified through numerical examples. The results indicate that, compared with conventional methods, the proposed method is more reasonable in planning location capacity, with the lowest system purchase cost and active power loss cost. The total planning cost of the proposed method is 7.716 million yuan/year, which helps to save energy and reduce emissions, and accelerate the achievement of the dual carbon goals.