This paper proposes a co-optimization generation and distribution planning model in microgrids in which simultaneous investment in generation, i.e., distributed generation (DG) and distributed energy storage (DES), and distribution, i.e., upgrading the existing distribution network, is considered. The objective of the proposed model is to minimize the microgrid total planning cost which compris...

In the rst part of the paper we present a framework for describing basic tech niques to improve the representation of a mixed integer programming problem We elaborate on identi cation of infeasibility and redundancy improvement of bounds and coe cients and xing of binary variables In the second part of the paper we discuss recent extensions to these basic techniques and elaborate on the investi...

A new mathematical model for the multistage distribution network expansion planning problem considering reliability is proposed in this paper. Decisions related to substation and branch are driven by minimization of total cost, which comprises investment operating costs including impact reliability. The features two main novelties. First, a set novel algebraic expressions devised standard index...

A linear-programming model for use in analysis and planning of multiobjective water resources systems is described in this paper. A typical system consists of reservoirs, hydropower stations, irrigated land, artificial and navigation channels, etc., over a reach of a river or a river basin. The linear programming approach is studied and compared with other approaches: mixed integer-linear dynam...

Microgrid and smart electrical grids are among the new concepts in power systems that support new technologies within themselves. Electric cars are some advanced technologies that their optimized use can increase grid efficiency. The modern electric cars sometimes, through the necessary infrastructure and proper management, can serve as an energy source to supply grid loads. This study was cond...

Post-hoc explanation methods for machine learning models have been widely used to support decision-making. One of the popular is Counterfactual Explanation (CE), also known as Actionable Recourse, which provides a user with perturbation vector features that alters prediction result. Given vector, can interpret it an "action" obtaining one's desired decision In practice, however, showing only of...