Abstract
The reliability of the power grid is a constant problem faced by those who operate, plan and study power systems. An alternative approach to this problem, and others related to the integration of renewable energy sources, is the microgrid. This research seeks to quantify the potential benefits of urban community microgrids, based on the development of planning models with deterministic and stochastic optimization approaches. The models ensure that supply meets demand whilst assuring the minimum cost of investment and operation. To verify their effectiveness, the planning of hundreds of microgrids was set in the city of Santiago de Chile. The most important results highlight the value of community association, such as: a reduction in investment cost of up to 35%, when community microgrids are planned with a desired level of reliability, compared to single residential household microgrids. This reduction is due to the diversity of energy consumption, which can represent around 20%, on average, of cost reduction, and to the Economies of Scale (EoS) present in the aggregation microgrid asset capacity, which can represent close to 15% of the additional reduction in investment costs. The stochastic planning approach also ensures that a community can prepare for different fault scenarios in the power grid. Furthermore, it was found that for approximately 90% of the planned microgrids with reliability requirements, the deterministic solution for the worst three fault scenarios is equivalent to the solution of the stochastic planning problem.
Highlights
The reduction is due to the diversity of energy consumption, which leads to a decrease in the PV capacity per customer as the number of clients per microgrid increases (Figure 6a): each box compiles the information of 100 different microgrids, where the triangle refers to the mean value of PV capacity per customer for the 100 microgrids, the orange line indicates the median value, and the limits of the rectangles represent the quartiles Q1 and Q3
In order to show the behavior of the diversity of energy consumption, Figure 6b shows the distributions with boxplot diagrams of monthly consumption per household, together with their standard deviations for each group of 1, 10, 20 and 100 residential households
Since the realistic residential demands obtained from the CREST Demand Model tool are different between loads, the planning models proposed in this research consider, among the most important factors, the formation of different groups of randomly selected residential clients, with which it is intended to collect the diversity in energy consumption due to the load aggregation
Summary
Power systems face an energy transition process that involves the concepts of smart grids, distributed generation and storage, demand side management and demand response [1]. Microgrids are defined as small electrical power systems that incorporate distributed generation, storage systems and controllable loads, as well as information and communication technologies for the local management of energy resources [3] They have the ability to operate both connected to the electricity grid and in islanded mode, for example, in the event of a contingency in the electricity grid [4]. In order for the benefits of microgrids to be perceived by the community, it is necessary that in the planning of microgrids, in addition to considering variables intrinsic to the traditional planning approach (such as the type and size of distributed generation technology), demand-side aspects must be covered [13] Some of these aspects involve the load profiles of each user in the community disaggregated by end use, as well as their diversity factor and flexible demand resources (interruptible and manageable loads). The proposed models fulfill the dual purpose of increasing the quality and reliability of the electrical power supply for a community that decides to protect itself from faults in the electricity grid, and facilitate the integration of small-scale renewable energy sources within the distribution systems
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