Generalized Planning Framework for Distributed Energy Resources in Smart Distribution Systems
Smart grid technologies provoke a major paradigm shift on how power systems are planned and operated. Part of planning this transition is envisioning the future system. Technical, social, environmental, and economical challenges are foreseen and tackled in the literature; however, no generalized planning framework that addresses the overall picture of different involved parties interests and their anticipated interactions to properly plan for a better and fair outcome has been developed. This work addresses the issue in several steps: 1) it provides a backbone framework architecture for asset sizing and allocation in the future smart distribution system, 2) it considers the daily optimal operation of these assets in the long-term planning problem, and 3) it considers the potential conflicts that happen on the long-term planning level and the operational level. This architecture requires the development of a framework capable of absorbing private investments, integrating new technologies, promote smart grid applications, and yet remains feasible to all involved parties.
Strategic analysis of involved stakeholders has been conducted. Proceeding from this analysis, deductions and conclusions about venues for promoting and allowing a smoother transition to the new paradigm are drawn. In addition, this analysis highlighted potential conflicts that are showcased in two different case studies. Discussion on how these conflicts affect the planning procedure and how to overcome them are proposed. The recommendations can be highlighted as follows: 1) promoting new smart grid technologies, 2) encourage communications and cooperation between involved parties, 3) consideration of daily optimal operation of assets to fully take advantage of their new active nature in order to better allocate them in the long-term planning problem, and 4) consideration of stakeholders interests in the planning phase in order to better absorb investments and move to the new paradigm.
In order to size and allocate assets in the long-term planning problem for the smart distribution system, first a building algorithm has been developed to size and allocate distributed generation (DG) units. This algorithm breaks the problem into two subproblems to overcome the modeling and computational challenges of the mixed integer nonlinear programming problem. The first subproblem is addressed using heuristic optimization techniques, namely a genetic algorithm, and the second involving deterministic analytical means of nonlinear optimization, utilizing the advancements made in branch-and-bound methods that provides a proven global optimal solution to non-convex problems. Considering the daily optimal operation and both electric utilities and investors objectives, the planning problem has been developed. Results show greater private investments absorption, reduced costs to both parties, and higher system performance due to lowered energy losses.