Step Towards Energy-Water Smart Microgrids; Buildings Thermal Energy and Water Demand Management Embedded in Economic Dispatch

被引:32
|
作者
Moazeni, Faegheh [1 ]
Khazaei, Javad [1 ,2 ,3 ]
Asrari, Arash [4 ]
机构
[1] Penn State Harrisburg, Civil & Environm Engn Dept, Middletown, PA 17057 USA
[2] Penn State Univ, Dept Elect Engn, State Coll, PA 16801 USA
[3] Penn State Univ, Architectural Engn Dept, State Coll, PA 16801 USA
[4] Southern Illinois Univ, Sch Elect Comp & Biomed Engn, Carbondale, IL 62901 USA
关键词
Buildings; Microgrids; Economics; Water resources; Batteries; Cost function; Wind energy generation; Economic Dispatch; Mixed Integer Linear Programming (MILP); Piecewise Linearization; Thermal Equilibrium; Water Demand Management; NEXUS;
D O I
10.1109/TSG.2021.3068053
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Energy, building, and water networks are three interlinked critical infrastructures that need to be operated cooperatively to maximize the smart grid's economic benefits. In this paper, a mixed-integer linear programming (MILP) formulation is proposed to approach the economic dispatch (ED) problem for smart grids embedded with interdependent water and energy networks. Energy management of various building applications is considered by intelligently controlling the indoor temperature during occupied and unoccupied hours. To optimize the demand of water distribution system, pump's nonlinear scheduling and hydraulic factors and daily water usage of buildings are added to the proposed model. Piecewise linear approximation of univariate and bivariate nonlinear functions is used to convert the nonlinear problem to an MILP formulation. Several case studies were conducted to examine the impact of indoor temperature settings of the buildings, speed of pumps, battery efficiency, and end of day (EoD) battery and tank constraints on economic dispatch of the microgrid system.
引用
收藏
页码:3680 / 3691
页数:12
相关论文
共 50 条
  • [31] Towards efficient energy management in smart grids considering microgrids with day-ahead energy forecasting
    Aslam, Sheraz
    Khalid, Adia
    Javaid, Nadeem
    ELECTRIC POWER SYSTEMS RESEARCH, 2020, 182 (182)
  • [32] Enhanced energy management in smart microgrids using hybrid optimization and demand response strategies
    Yang, Lei
    Wu, Lile
    Li, Genzhu
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2025, 164
  • [33] Intelligent Residential Energy Management System for Dynamic Demand Response in Smart Buildings
    Arun, S. L.
    Selvan, M. P.
    IEEE SYSTEMS JOURNAL, 2018, 12 (02): : 1329 - 1340
  • [34] Energy-Water Management System Based on MPC for a Greenhouse in a Mapuche Indigenous Community
    Endo, Alvaro
    Parra, Sebastian
    Cartagena, Oscar
    Saez, Doris
    Munoz, Carlos
    Huircan, Juan Ignacio
    APPLIED SCIENCES-BASEL, 2023, 13 (08):
  • [35] Saving Energy From Urban Water Demand Management
    Escriva-Bou, A.
    Lund, J. R.
    Pulido-Velazquez, M.
    WATER RESOURCES RESEARCH, 2018, 54 (07) : 4265 - 4276
  • [36] Water and Energy Demand Management in Pressurized Irrigation Networks
    Angel Pardo, Miguel
    Riquelme, Adrian J.
    Jodar-Abellan, Antonio
    Melgarejo, Joaquin
    WATER, 2020, 12 (07)
  • [37] Water and energy demand management in pressurized irrigation networks
    Pardo M.A.
    Riquelme A.J.
    Jodar-Abellan A.
    Melgarejo J.
    Water (Switzerland), 2020, 12 (07):
  • [38] Towards Renewable energy targets for the Middle East and North African region: A decarbonization assessment of energy-water nexus
    Adun, Humphrey
    Ishaku, Hamagham Peter
    Ogungbemi, Ayomide Titus
    JOURNAL OF CLEANER PRODUCTION, 2022, 374
  • [39] IoT Energy Management for Smart Homes' Water Management System
    Corte, P.
    Sampaio, H.
    Lussi, E.
    Westphall, C.
    JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2023, 32 (13)
  • [40] Robust Energy-Water Management System with Prediction Interval Based on Deep Learning
    Rojas, Lucas
    Ocaranza, Javier
    Cartagena, Oscar
    Saez, Doris
    Daniele, Linda
    Ahumada, Constanza
    2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN, 2023,