Abstract
The planning and operation of Smart Grid projects is an issue that has increased in complexity and requires further analysis. This is due to the increase of distributed generation sources, generation with renewable sources, storage systems, and a disarticulation of information between the different levels in the sector and the stakeholders. All these factors lead to the inherent difficulty of defining appropriate models that help decision making. This paper proposes a bi-level optimization model to solve the problem of planning and operation of microgrid projects, as these can be considered as an ideal small-scale prototype of the so-called Smart Grids. In this bi-level scheme, the problem of planning or design of the microgrid is formulated at the upper level, while the problem of power dispatch or operation of the units is described at the lower level. The proposed multilevel multi-objective decision model is inspired by the System of System (SoS) concept in order to integrate qualitative and quantitative decision-making tools. Likewise, Key Performance Indicators (KPIs) are used for the detailed and continuous monitoring of any project. The presented model is applied using the information of an electrically isolated microgrid on the Colombian Pacific coast.Keywords: Smart Grids, Bi-level optimization, Decision Making, Key Performance Indicators, QFD, Energy planning and management.JEL Classifications: C61, D70, L94, Q42.DOI: https://doi.org/10.32479/ijeep.9343
Highlights
One of the advantages of this work is the use of key performance indicators (KPIs), which are closely linked to strategic objectives and allow answering critical business questions set before the proposed optimization model
The model considers the development of a metaheuristic particle swarm optimization (PSO) algorithm
The model demonstrates the importance of using qualitative decision-making tools such as fuzzy Quality Function Deployment (QFD) and AHP, which can transform the judgments of experts into mathematical representations to introduce relative importance weights into the optimization algorithm
Summary
Two-level decision techniques (bi-level) are commonly used in studies of microgrid projects where it is necessary to consider planning and operation in a coordinated manner In these models, decision makers try to optimize their respective objective functions independently, but decisions are affected in the decision space of the other level. In (Stojiljković, 2017) the authors present a methodology to solve energy supply problems using a multi-objective bi-level optimization model, where the upper level defines the design and energy policies, while the lower level defines the operation. This paper proposes a bi-level planning model that combines problems of Planning/Design at the upper level (Leader) and Operation at the lower level (Follower) with the development of a multi-objective bi-level metaheuristic algorithm by particle swarm (BLMOPSO). One of the advantages of this work is the use of KPIs (up to twelve for this study), which are closely linked to strategic objectives and allow answering critical business questions set before the proposed optimization model
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