Multi-objective stochastic programming energy management for integrated INVELOX turbines in microgrids: A new type of turbines

Shaterabadi, Mohammad; Jirdehi, Mehdi Ahmadi

doi:10.1016/j.renene.2019.08.002

Cited by 45 publications

(17 citation statements)

References 54 publications

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“…The amount of producing power by portable IWTs has been defined by Equation (15). [ 42 ]

P_{IWT}^{PORT} (t) = (\begin{array}{l} 0 \forall t : V^{Cut‐i n^{'}} \geq V_{t} and V^{Cut‐i n^{'}} \leq V_{t} \\ 0.5 \times ρ^{'} \times A^{'} \times η^{W^{'}} \times K_{p}^{'} \times {false(V_{t} \times S_{R}^{'} false)}^{3} \forall t : V^{Cut‐i n^{'}} \leq V_{t} \leq V^{Cut‐i n^{'}} \end{array})

P_{Battery}^{PORT} (t) = \sum_{t = 1}^{T} (P_{IWT}^{PORT} (t))

…”

Section: Problem Modelingmentioning

confidence: 99%

“…Finally, IWT and CCUS are utilized in the last scenario to calculate the effect of them on the objective function. The overall expenditure for the aforementioned scenarios is thus expressed, respectively, by Equation (20)–(22) [ 23,42a ]

{T C (cost) = \sum_{t = 1}^{T} (\begin{array}{l} F_{CHP} false(t false) + F_{Wind} false(t false) + F_{Boiler} false(t false) + F_{PV} false(t false) \\ + F_{Buy} false(t false) - F_{Sell} false(t false) + F_{ES} false(t false) + F_{TS} false(t false) + F_{MT} false(t false) \end{array})}

{T C (cost) = \sum_{t = 1}^{T} (\begin{array}{l} F_{CHP} false(t false) + F_{IWT} false(t false) + F_{IWT}^{PORT} false(t false) + F_{Boiler} false(t false) + \\ F_{PV} false(t false) + F_{Buy} false(t false) - F_{Sell} false(t false) + F_{ES} false(t false) + F_{TS} false(t false) + F_{MT} false(t false) \end{array})}

{T C (cost) = \sum_{t = 1}^{T} (\begin{array}{l} F_{CHP} false(t false) + F_{IWT<...>} \end{array}

…”

Section: Problem Formulationmentioning

confidence: 99%

“…Total microgrid and MG emissions are demonstrated by Equation (34) [42a]

TP (Emission) = \sum_{t = 1}^{T} ({POL}_{CHP} (t) + {POL}_{MT} (t) + {POL}_{MG} (t) + {POL}_{Boiler} (t))

…”

Section: Problem Formulationmentioning

confidence: 99%

“…CHP, Boiler, MT, and MG pollutions have been described by Equation (35)–(38), respectively. [ 23,42a ]

{POL}_{CHP} (t) = \sum_{t = 1}^{T} P_{CHP} (t) \times {POLF}_{CHP} \times ψ

{POL}_{Boiler} (t) = \sum_{t = 1}^{T} P_{Boiler} (t) \times {POLF}_{Boiler} \times ψ

{POL}_{MT} (t) = \sum_{t = 1}^{T} P_{MT} (t) \times {POLF}_{MT} \times ψ

{POL}_{MG} (t) = \sum_{t = 1}^{T} P_{Buy} (t) \times {POLF}_{MG} \times ψ

…”

Section: Problem Formulationmentioning

confidence: 99%

See 3 more Smart Citations

Incentive Programs Caused by the Carbon Capture Utilization and Storage Technology Profit's Effect: Optimal Configuration and Energy Planning of Hybrid Microgrid Involving INVELOX Turbine

Jirdehi

Shaterabadi

2020

Energy Tech

Self Cite

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Herein, optimal configuration and microgrid's energy control based on day-ahead planning is proposed. For this purpose, fossil fuel resources are equipped with carbon capture utilization and storage (CCUS) technologies, and INVELOX turbines are proposed in microgrid's planning. The microgrid's overall contamination and cost are considered as objective functions. To encourage the consumers to utilize renewable resources, obtained profit from CCUS is assigned as incentive programs for buying their extra energy. Also, the problem is modeled as a mixed-integer linear programming (MILP), and the epsilon constraint and fuzzy satisfying approach are utilized to tackle and accomplish the best and optimal solution. The outcomes show that overall costs and contamination are

show abstract

“…The amount of producing power by portable IWTs has been defined by Equation (15). [ 42 ]

P_{IWT}^{PORT} (t) = (\begin{array}{l} 0 \forall t : V^{Cut‐i n^{'}} \geq V_{t} and V^{Cut‐i n^{'}} \leq V_{t} \\ 0.5 \times ρ^{'} \times A^{'} \times η^{W^{'}} \times K_{p}^{'} \times {false(V_{t} \times S_{R}^{'} false)}^{3} \forall t : V^{Cut‐i n^{'}} \leq V_{t} \leq V^{Cut‐i n^{'}} \end{array})

P_{Battery}^{PORT} (t) = \sum_{t = 1}^{T} (P_{IWT}^{PORT} (t))

…”

Section: Problem Modelingmentioning

confidence: 99%

{T C (cost) = \sum_{t = 1}^{T} (\begin{array}{l} F_{CHP} false(t false) + F_{Wind} false(t false) + F_{Boiler} false(t false) + F_{PV} false(t false) \\ + F_{Buy} false(t false) - F_{Sell} false(t false) + F_{ES} false(t false) + F_{TS} false(t false) + F_{MT} false(t false) \end{array})}

{T C (cost) = \sum_{t = 1}^{T} (\begin{array}{l} F_{CHP} false(t false) + F_{IWT} false(t false) + F_{IWT}^{PORT} false(t false) + F_{Boiler} false(t false) + \\ F_{PV} false(t false) + F_{Buy} false(t false) - F_{Sell} false(t false) + F_{ES} false(t false) + F_{TS} false(t false) + F_{MT} false(t false) \end{array})}

{T C (cost) = \sum_{t = 1}^{T} (\begin{array}{l} F_{CHP} false(t false) + F_{IWT<...>} \end{array}

…”

Section: Problem Formulationmentioning

confidence: 99%

“…Total microgrid and MG emissions are demonstrated by Equation (34) [42a]

TP (Emission) = \sum_{t = 1}^{T} ({POL}_{CHP} (t) + {POL}_{MT} (t) + {POL}_{MG} (t) + {POL}_{Boiler} (t))

…”

Section: Problem Formulationmentioning

confidence: 99%

“…CHP, Boiler, MT, and MG pollutions have been described by Equation (35)–(38), respectively. [ 23,42a ]

{POL}_{CHP} (t) = \sum_{t = 1}^{T} P_{CHP} (t) \times {POLF}_{CHP} \times ψ

{POL}_{Boiler} (t) = \sum_{t = 1}^{T} P_{Boiler} (t) \times {POLF}_{Boiler} \times ψ

{POL}_{MT} (t) = \sum_{t = 1}^{T} P_{MT} (t) \times {POLF}_{MT} \times ψ

{POL}_{MG} (t) = \sum_{t = 1}^{T} P_{Buy} (t) \times {POLF}_{MG} \times ψ

…”

Section: Problem Formulationmentioning

confidence: 99%

See 2 more Smart Citations

Incentive Programs Caused by the Carbon Capture Utilization and Storage Technology Profit's Effect: Optimal Configuration and Energy Planning of Hybrid Microgrid Involving INVELOX Turbine

Jirdehi

Shaterabadi

2020

Energy Tech

Self Cite

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show abstract

“…In 2019, the cities accounted for more than 75% of energy consumed across China. This proportion is expected to surpass 80% in 2029 [1][2][3][4][5][6]. To balance urban development with environment protection and energy consumption, it is necessary to complete the shift from the traditional model of urban construction to the planned construction of a composite system between smartness and energy, along with the rise of smart cities.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Optimization of Digital Management for Renewable Energies in Smart Cities

Huang¹,

Huang²,

Huang³

2020

JESA

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Smart cities mark the shift from the traditional model of urban construction to the planned construction of a composite system between smartness and energy. Considering the defects of renewable energies, e.g., intermittency, randomness, and low dispatchability, it is imperative to explore the digital and unified management of urban renewable energies. Therefore, this paper presents a multi-objective optimization algorithm for digital management, which can quantify the multiple energy models of smart cities. Firstly, the dimensions of renewable energy construction in smart cities were detailed, and the functions, hierarchy, and data flows of the digital management system for renewable energies were plotted in turn. After that, the output probability models of typical renewable energy power generation systems were established, plus the objective functions of digital management for renewable energies. Finally, particle swarm optimization (PSO) was combined with genetic algorithm (GA) for multi-objective optimization of the digital management for renewable energies in smart cities. The proposed models and algorithm were proved effective through experiments.

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Energy Management Strategies of a Microgrid

Biswas,

Bhattacharjee,

Das

et al. 2023

Urban Energy Systems

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Multi-objective stochastic programming energy management for integrated INVELOX turbines in microgrids: A new type of turbines

Cited by 45 publications

References 54 publications

Incentive Programs Caused by the Carbon Capture Utilization and Storage Technology Profit's Effect: Optimal Configuration and Energy Planning of Hybrid Microgrid Involving INVELOX Turbine

Incentive Programs Caused by the Carbon Capture Utilization and Storage Technology Profit's Effect: Optimal Configuration and Energy Planning of Hybrid Microgrid Involving INVELOX Turbine

Multi-objective Optimization of Digital Management for Renewable Energies in Smart Cities

Energy Management Strategies of a Microgrid

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