Nonlinear Power Injection Sensitivity Analysis in Power Systems: An Effective Strategy for Distributed Source Allocation

Distributed generation in power systems is currently attracting significant attention as a means to reduce energy generation costs through the exploitation of low-cost decentralized sources. Cost reduction becomes especially relevant when a large portion of the energy supplied by a centralized generator is replaced by energy from a few high-power distributed sources. However, the effectiveness and safety of this approach critically depend on the proper allocation of distributed generators. To this end, this paper presents a novel sensitivity analysis for system losses that highlights the nonlinear dependencies on power-injecting sources. It is shown that the parameters of the nonlinear model allow easy identification of a small subset of grid buses that are suitable candidates for large-power injection. At these buses, source sizing can be determined using standard optimal power flow techniques that minimize the energy cost function. The proposed allocation strategy is validated on the IEEE 69 and 85 benchmark bus grids, and its robustness is further confirmed through simulations that account for stochastic load fluctuations. Comparison with state of the art and robust source allocation approaches, such as the Iterative Search Method, shows that for similar accuracy the proposed method is two/three orders of magnitude faster.