Risk‐constrained energy management of PV integrated smart energy hub in the presence of demand response program and compressed air energy storage
Multi‐carrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among different energy hubs’ facilities and various operational parameters on the scheduling of the energy hub systems. This paper deals with the problem o...
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| Veröffentlicht in: | IET renewable power generation Jg. 13; H. 6; S. 998 - 1008 |
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| Sprache: | Englisch |
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The Institution of Engineering and Technology
01.04.2019
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| ISSN: | 1752-1424, 1752-1416, 1752-1424 |
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| Abstract | Multi‐carrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among different energy hubs’ facilities and various operational parameters on the scheduling of the energy hub systems. This paper deals with the problem of optimal scheduling of smart residential energy hub (SREH) considering the different uncertain parameters. The effect of the market prices, demands and solar radiation uncertainties on the SREH scheduling problem is characterised through a risk‐constrained two‐stage stochastic programming model. The objective of the proposed scheduling problem is to determine the least‐cost 24 h operation of the facilities that would cover the cooling, thermal and electrical demands. The Monte Carlo simulation method is applied to model the inaccuracies of solar radiation, energy demands, and electricity market prices. Additionally, a proper scenario‐reduction algorithm is employed to reduce the number of scenarios and simulation burden. The proposed approach evaluates the impacts of different values of risk aversion parameter and the utility of the demand response program on the optimal solution of the proposed PV integrated SREH scheduling. Finally, an illustrative example is provided to confirm the efficiency and the applicability of the proposed approach. |
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| AbstractList | Multi‐carrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among different energy hubs’ facilities and various operational parameters on the scheduling of the energy hub systems. This paper deals with the problem of optimal scheduling of smart residential energy hub (SREH) considering the different uncertain parameters. The effect of the market prices, demands and solar radiation uncertainties on the SREH scheduling problem is characterised through a risk‐constrained two‐stage stochastic programming model. The objective of the proposed scheduling problem is to determine the least‐cost 24 h operation of the facilities that would cover the cooling, thermal and electrical demands. The Monte Carlo simulation method is applied to model the inaccuracies of solar radiation, energy demands, and electricity market prices. Additionally, a proper scenario‐reduction algorithm is employed to reduce the number of scenarios and simulation burden. The proposed approach evaluates the impacts of different values of risk aversion parameter and the utility of the demand response program on the optimal solution of the proposed PV integrated SREH scheduling. Finally, an illustrative example is provided to confirm the efficiency and the applicability of the proposed approach. |
| Author | Abapour, Mehdi Asadi, Somayeh Dolatabadi, Amirhossein Mohammadi‐Ivatloo, Behnam Jadidbonab, Mohammad |
| Author_xml | – sequence: 1 givenname: Mohammad surname: Jadidbonab fullname: Jadidbonab, Mohammad organization: University of Tabriz – sequence: 2 givenname: Amirhossein orcidid: 0000-0001-7970-2408 surname: Dolatabadi fullname: Dolatabadi, Amirhossein organization: University of Tabriz – sequence: 3 givenname: Behnam surname: Mohammadi‐Ivatloo fullname: Mohammadi‐Ivatloo, Behnam email: bmohammadi@tabrizu.ac.ir organization: University of Tabriz – sequence: 4 givenname: Mehdi surname: Abapour fullname: Abapour, Mehdi organization: University of Tabriz – sequence: 5 givenname: Somayeh surname: Asadi fullname: Asadi, Somayeh organization: Pennsylvania State University |
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| SubjectTerms | boiler boilers cogeneration combined heat and power unit compressed air energy storage compressed air energy storage system conditional value‐at‐risk methodology cooling demands demand response program demand side management electrical demands electrical power electricity market prices energy hub system scheduling energy management systems future energy systems Monte Carlo methods Monte Carlo simulation method multicarrier energy systems operational parameters optimal scheduling photovoltaic integrated system photovoltaic power systems power generation economics power generation scheduling power markets power unit pricing PV integrated smart energy hub PV integrated SREH scheduling PV system risk analysis risk aversion parameter risk‐constrained energy management risk‐constrained two‐stage stochastic programming model scenario‐reduction algorithm smart power grids smart residential energy hub solar radiation solar radiation uncertainties stochastic programming thermal demands thermal energy storage time 24.0 hour |
| Title | Risk‐constrained energy management of PV integrated smart energy hub in the presence of demand response program and compressed air energy storage |
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