This chapter presents a detailed formulation of the optimal power flow (OPF) problem in monopolar DC networks, adopting a nodal representation grounded in graph theory and circuit analysis. The chapter begins by introducing the mathematical foundations of DC power systems, including the construction of the nodal conductance matrix and the formulation of the power flow equations. A representative example is used to highlight the nonlinearities and challenges introduced by constant power loads, particularly in the context of the power balance constraints. The chapter then explores how the power flow problem can be reformulated as a convex optimization model using a potential function approach, offering a geometrical interpretation that facilitates analysis and solution. Additionally, a derivative-free iterative method based on successive approximations is developed to solve the power flow equations efficiently. Building upon this foundation, the chapter extends the OPF formulation to a multiperiod framework, incorporating time-varying variables such as generation, load, and network constraints. This generalized model includes power balance, current flow limits, voltage regulation, and device capability constraints, culminating in a comprehensive multiperiod optimization problem aimed at minimizing total energy losses. Finally, a classification of existing solution techniques is presented, emphasizing the role of convex optimization methods—both direct and indirect—as robust and mathematically grounded alternatives to heuristic approaches for solving the OPF problem in DC networks.