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Reliability is an essential factor in distribution networkt expansion planning. However, standard distribution reliability assessment techniques rely on quantifying the impact of a pre-specified set of events on service continuity through the simulation of component outages, one at a time. Due to such a simulation-based nature, the incorporation of reliability into distribution network expansion planning has customarily required the application of heuristic and metaheuristic approaches. Recently, alternative mixed-integer linear programming (MILP) models have been proposed for distribution network expansion planning considering reliability. Nonetheless, such models suffer from either low computational efficiency or over-simplification. To overcome these shortcomings, this paper proposes an enhanced MILP model for multistage reliability-constrained distribution network expansion planning. Leveraging an efficient, yet accurate reliability evaluation model, proposing a customized technique for effectively imposing radial operation, as well as utilizing pragmatic measures to model reliability-related costs are the salient features of this work. In this respect, practical reliability-related costs are considered based on reliability incentive schemes and the revenue lost due to undelivered energy during customer outages. The proposed planning approach is tested on four networks with 24, 54, 86, and 138 nodes to illustrate its efficiency and applicability. [ABSTRACT FROM AUTHOR]

The calculation of standard reliability indices is critical for assessing quality service and guiding the planning and operation of distribution systems. Traditionally, such calculation has relied on the application of analytical methods based on simulation techniques, which preclude the use of exact methodologies when reliability assessment is incorporated into operation and planning models. This shortcoming has been recently addressed by the development of two optimization-based approaches for the analytical reliability assessment of distribution systems. Unfortunately, both methods are either incomplete or computationally expensive as compared with those based on simulation. In order to overcome these issues, this paper presents a novel and efficient algebraic approach to calculate the standard network-dependent reliability indices of distribution systems. As a distinctive feature over previous non-simulation-based methods, no optimization process is involved. Thus, the proposed approach relies on the solution of a set of linear equations for which effective algorithms are available. Several benchmarks including a real-life 1080-node system have been used to demonstrate the computational superiority of the proposed method. The successful numerical experience supports the suitability of the proposed algebraic model for reliability-constrained distribution system operation and planning. [ABSTRACT FROM AUTHOR]

This paper investigates the multistage expansion planning problem of a distribution network considering reliability. Thus, the best alternative, location, and installation time for the candidate assets are identified while jointly accounting for economic and reliability aspects. As a major salient feature, the conventional simulation-based reliability assessment is equivalently implemented through algebraic expressions whereby the effect of the network topology is explicitly represented by decision variables of the optimization process. For expository purposes, the focus is placed on the expected energy not supplied, which is a widely-used metric for reliability assessment. The resulting optimization problem is cast as an instance of mixed-integer linear programming. Hence, unlike existing heuristic and metaheuristic solution techniques for reliability-constrained distribution system planning, the proposed approach is finitely convergent to the optimal solution and can be readily implemented using commercially available software. Simulation results show the effective performance of the proposed methodology. [ABSTRACT FROM PUBLISHER]