Abstract

In this paper, a collective residential building is considered in which the following points are taken into consideration: (i) a flexibility value of Contract Power (CP) is considered for each consumer; (ii) it is assumed a single CP for the entire building; (iii) an energy resource manager entity is considered to manage the energy resources in the residential building, such as Electric Vehicles (EVs), Photovoltaic (PV) generation system, and the Battery Energy Storage System (BESS). Taking into consideration the previous assumptions, the major goal of this work is to minimize the electricity consumption costs of the residential building by using a Multi-Objective Mixed-Binary Linear Programming (MOMBLP) formulation. The objective function of the MOMBLP model minimizes the electricity cost consumption of each apartment. Then, a Goal Programming (GP) strategy is applied to find the most appropriate solutions for the proposed MOMBLP model. Finally, the performance of the suggested model is evaluated by comparing the obtained results from a Single-Objective Mixed-Binary Linear Programming (SOMBLP) approach in which the whole building consumption cost is minimized. The results show that using the GP strategy a reduction of 7.5% in the total annual energy consumption is verified in comparison with SOMBLP. Moreover, the GP approach leads to fair benefit among building consumers, by finding a solution with less distance from the desired level.

Highlights

  • A significant part of global greenhouse gas emissions is related to energy consumption which is expected to rise around 40% in the following decades [1]

  • The results suggest that the Goal Programming (GP) approach is very promising since it can reduce the total annual energy consumption when comparing with the conteurpart SingleObjective Mixed-Binary Linear Programming (SOMBLP) model, and by identifying a solution that is closer to the ideal point, leading to a fair benefit among the building users

  • The proposed MultiObjective Mixed-Binary Linear Programming (MOMBLP) is reformulated by a Goal Programming (GP) problem to obtain the most appropriate solution

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Summary

INTRODUCTION

A significant part of global greenhouse gas emissions is related to energy consumption which is expected to rise around 40% in the following decades [1]. The main goal of the optimization model we develop is to reduce the total electricity consumption cost by minimizing the cost of each consumer in which each apartment has EV and PV generation and equipped by BESS and EMS. Scalarization approaches are popular methods to determine the Pareto solution Multi-Objective Optimization Problems (MOOP) [9], [10]. The main contribution of this work is to apply the GP approach to find the most appropriate solutions for the proposed MOMBLP model. The results suggest that the GP approach is very promising since it can reduce the total annual energy consumption when comparing with the conteurpart SingleObjective Mixed-Binary Linear Programming (SOMBLP) model, and by identifying a solution that is closer to the ideal point (main goal), leading to a fair benefit among the building users.

RELATED WORK
REQUIRED PARAMETERS AND VARIABLES
MATHEMATICAL FORMULATION
15 Minutes
CONCLUSION
Findings
GP Method MBLP Method
Full Text
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