Abstract

With the development of electronic infrastructures and communication technologies and protocols, electric grids have evolved towards the concept of Smart Grids, which enable the communication of the different agents involved in their operation, thus notably increasing their efficiency. In this context, microgrids and nanogrids have emerged as invaluable frameworks for optimal integration of renewable sources, electric mobility, energy storage facilities and demand response programs. This paper discusses a DC isolated nanogrid layout for the integration of renewable generators, battery energy storage, demand response activities and electric vehicle charging infrastructures. Moreover, a stochastic optimal scheduling tool is developed for the studied nanogrid, suitable for operators integrated into local service entities along with the energy retailer. A stochastic model is developed for fast charging stations in particular. A case study serves to validate the developed tool and analyze the economical and operational implications of demand response programs and charging infrastructures. Results evidence the importance of demand response initiatives in the economic profit of the retailer.

Highlights

  • The Smart Grid paradigm requires active participation and coordination of all the agents involved in the electric system [1,2]

  • Because of the heterogeneity and conflicting interests of the different agents involved in the NG operation, their coordination is frequently addressed in a centralized fashion by the grid operator

  • The last element of the expenditures stands for the fuel cost of diesel engine generators (DEGs), which can be calculated as a quadratic function of the energy generated, as follows [39]: 2

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Summary

Introduction

The Smart Grid paradigm requires active participation and coordination of all the agents involved in the electric system [1,2]. With the advent of this concept, nanogrids (NGs) have emerged as an invaluable framework for the integration of renewable generation, electric vehicles (EVs), storage facilities and demand response (DR) programs [3,4,5,6]; as well as for electrical supplying of remote isolated areas [7] In this context, the optimal coordination of the agents involved requires deploying advanced communication infrastructures and electronic interfaces on either AC, DC or hybrid networks [8,9,10]. Electronics 2021, 10, 2484 entity structure along with the local retailer This way, in contrast to most of the existing scheduling tools for similar grids which are devoted to minimizing the operational cost, the developed formulation aims at maximizing the benefits obtained by the retailer optimally coordinating on-site generators, storage facilities, flexible consumers and public charging infrastructures.

Description of the NG under Study
Assumptions
Objective Function
DEG Modelling
PV Modelling
WT Modelling
BES Modelling
Shiftable Consumers Modeling
Public EV Charging Station Modeling
NG Balance
3.10. Optimization Problem
Uncertainties Modeling
Predictable Parameters
EV Demand Modeling
Case Study
Results
Conclusions and Future Works
Full Text
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