Stochastic framework for peak demand reduction opportunities with solar energy for manufacturing facilities

被引:7
|
作者
Peinado-Guerrero, Miguel A. [1 ]
Villalobos, Jesus R. [1 ]
Phelan, Patrick E. [1 ]
Campbell, Nicolas A. [1 ]
机构
[1] Arizona State Univ, Ind Assessment Ctr, Tempe, AZ 85281 USA
基金
美国能源部;
关键词
Demand-side management; Markov chains; Stochastic; Demand response; Renewable integration; SIDE MANAGEMENT; UNCERTAINTY;
D O I
10.1016/j.jclepro.2021.127891
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Demand-side management has gained traction as a means for energy service providers to persuade their customers to change the pattern of their energy use. The aim is typically to create a balance between electrical supply and demand, particularly with the introduction of variable distributed resources such as solar. This paper proposes a non-intrusive methodology for evaluating an energy customer's potential for participation in demandside management programs with a focus on manufacturing facilities. The methodology rests on modeling the stochasticity of individuals' energy loads to estimate when peak demand is most likely to occur. The proposed methodology is applied to the design of solar photovoltaic power generation for the purpose of maximum demand-side peak reduction in the targeted facility. The results of a case study reveal that the proposed methodology enabled a user to attain 2.5% more cost savings, while reducing the amount of electrical energy sold back to the utility company by 45.8%.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Peak power demand reduction for combined manufacturing and HVAC system considering heat transfer characteristics
    Dababneh, Fadwa
    Li, Lin
    Sun, Zeyi
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2016, 177 : 44 - 52
  • [22] The EPR experiment in the energy-based stochastic reduction framework
    Silman, J.
    Machnes, S.
    Shnider, S.
    Horwitz, L. P.
    Belenkiy, A.
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2008, 41 (25)
  • [23] Opportunities for peak shaving the energy demand of ship-to-shore quay cranes at container terminals
    Harry Geerlings
    Robert Heij
    Ron van Duin
    Journal of Shipping and Trade, 3 (1)
  • [24] A rolling horizon stochastic programming framework for the energy supply and demand management in microgrids
    Silvente, Javier
    Kopanos, Georgios M.
    Espuna, Antonio
    12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND 25TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT C, 2015, 37 : 2321 - 2326
  • [25] Energy storage system scheduling for peak demand reduction using evolutionary combinatorial optimisation
    Agamah, Simon U.
    Ekonomou, Lambros
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2017, 23 : 73 - 82
  • [26] Evaluating uncertainty of shared energy in solar energy communities using a stochastic simulation framework
    De Bettin, F.
    Minuto, F. D.
    Schiera, D. S.
    Lanzini, A.
    RENEWABLE ENERGY, 2025, 243
  • [27] Energy Storage Versus Demand Side Management for Peak-Demand Reduction at the Hawaii Ocean Science and Technology Park
    Manoharan, Yogesh
    Headley, Alexander
    Olson, Keith
    Sombardier, Laurence
    Schenkman, Benjamin
    PROCEEDINGS OF THE ASME 2021 15TH INTERNATIONAL CONFERENCE ON ENERGY SUSTAINABILITY (ES2021), 2021,
  • [28] DECREASE IN OFF-PEAK ELECTRICAL ENERGY DEMAND BY AGROINDUSTRIES DUE TO PHOTOVOLTAIC SOLAR GENERATION
    Viana, Lucas de A.
    Oliveira Filho, Deity
    Toledo, Olga M.
    da Silva, Samuel C.
    Dalvi, Giovanni G.
    ENGENHARIA AGRICOLA, 2019, 39 (04): : 537 - 547
  • [29] Strategies for beneficial electric vehicle charging to reduce peak electricity demand and store solar energy
    Needell, Zachary
    Wei, Wei
    Trancik, Jessika E.
    CELL REPORTS PHYSICAL SCIENCE, 2023, 4 (03):
  • [30] Performance assessment of active insulation systems in residential buildings for energy savings and peak demand reduction
    Kunwar, Niraj
    Salonvaara, Mikael
    Iffa, Emishaw
    Shrestha, Som
    Hun, Diana
    APPLIED ENERGY, 2023, 348