Abstract

Abstract

Abstract

Abstract
Planning the expansion and the new topology of distribution networks requires knowing the location and characterization of the load as well as its future growth. Spatial load forecasting is a key tool in this task, providing high spatial resolution and adequate temporal granularity. Nowadays, with the penetration of distributed energy resources, multiple microgrid connection strategies, and implementation of self-healing and protection schemes, it is necessary to identify load blocks to plan the new active network architecture. Based on spatial load forecasting information, this paper proposes a graph partitioning technique to create load clusters in the distribution feeders. A weighted graph is constructed by means of a minimum spanning tree that allows to consider adjacency relations. The results of the simulation, carried out in a real distribution network, have demonstrated the effectiveness of the proposed method.

Abstract
The location of a new substation is a key factor in the expansion of electrical distribution systems. This location is strategic from the point of view of the costs associated with energy supply; therefore, a holistic and integral planning of sub-transmission and primary distribution subsystems requires the development of suitable optimization methods to support the decision process. Although future electric load growth is a critical factor to define capacity and location of new substations, other technical, environmental, soil characteristics, risk, social, and administrative criteria that influence the final location are also crucial. A multicriteria decision analysis based on geographic information system is proposed in this paper to combine those criteria taking into account decision makers' preferences and physical restrictions on land use. The main contributions of this paper are the identification of the criteria and the analysis of service areas in existing substations to impose constraints on the problem. A spatial heat map that facilitates the visual interpretation of the spatial relations of the criteria is produced based on a suitability score. The proposed method was evaluated in the service area of an Ecuadorian distribution energy utility. It was found that the two more important criteria are the electric load density and the distance to subtransmission network with weights of 44% and 23%, respectively. The proposed analysis is able to identify ideal locations for new substations, which can be used by the planner to find the best long-term network expansion alternative.

Abstract
The growing adoption of photovoltaic systems as a result of government incentives and the cost-effectiveness of the technology will bring significant environmental benefits and help countries meeting their international commitments in terms of renewables share. Nevertheless, an unsuitable site location could compromise its production and lead to a poor integration. An optimal location of photovoltaic systems must account for factors such as land use restrictions, orography, environmental, climatic limitations, and proximity to infrastructure. A key aspect that needs to be further researched is the influence of the electric demand requirement and its spatial distribution on the enhancement of photovoltaic integration. This paper proposes a novel approach to define optimal sites for photovoltaic plants, connected to the medium-voltage level, using a geographic information system based multi-criteria decision making and spatial overlay with electric load. The main feature of this work is the use of high-resolution information to spatially characterize the demand and make a density analysis. The performance of the proposed method is assessed in the service area of an Ecuadorian power utility. Scenarios considering solar potential and the massive penetration of a new type of load are assessed to define the photovoltaic sites that enhance the integration of renewable sources in the case study.