Optimal economic dispatch of FC-CHP based heat and power micro-grids

Nazari-Heris, Morteza; Abapour, Saeed; Mohammadi‐Ivatloo, Behnam

doi:10.1016/j.applthermaleng.2016.12.016

Cited by 216 publications

(70 citation statements)

References 40 publications

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“…Moreover, the startup/shutdown expenditures are represented in Table . The factors of objectives are quoted from the work of Nazari‐Heris et al…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Moreover, the startup/shutdown expenditures are represented in Table 6. The factors of objectives are quoted from the work of Nazari-Heris et al 43 Table 7 listed Pareto-optimal answers in the case of the first scenario. By considering 0.5 for the step size, the iteration number of the method for producing the Pareto-optimal answer will be 21.…”

Section: Numerical Resultsmentioning

confidence: 99%

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New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power

Zeng

Berti

2019

Computational Intelligence

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Microgrids can be assumed as a solution model for green energy sources, energy storage systems, and combined heat and power (CHP) systems. In this work, the cost and emission minimization based on a demand response (DR) program is considered an optimization problem. To solve the mentioned problem a new multiobjective optimization algorithm (improved particle swarm optimization) is proposed based on a fuzzy mechanism to select the optimal value. The microgrid system includes two CHP units, fuel cell and battery systems, and the heat buffer tank. In this problem, two different feasible operating regions have been assumed in CHPs. Accordingly, to decrease the operational cost, time‐of‐use, and real‐time pricing DR programs have been simulated, and the impacts of the mentioned models are evaluated overload profiles. The effectiveness of proposed models has been applied on different cases studies by different scenarios. The proposed model solved the DR program, time of use‐DR and real‐time pricing‐DR problems. The proposed model could reduce the cost about 10%.

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“…Moreover, the startup/shutdown expenditures are represented in Table . The factors of objectives are quoted from the work of Nazari‐Heris et al…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power

Zeng

Berti

2019

Computational Intelligence

View full text Add to dashboard Cite

show abstract

“…Moreover, the daily thermal demands, electrical demands, wind turbine output, and PV output, which are generated by the Monte Carlo simulation, are displayed in Figure 2. Finally, the emissions generated by different generators and the standard grade of pollutant values are based on previous work [32]. To optimize the PSO model, the related parameters are defined as follows: the number of particles is 250; the largest number of iterations is 300; the maximum and the minimum speed and positions are ±1 and ±5, respectively; and the inertia weight c1 and c2 used in this paper are 1.3 and 2.8, respectively.…”

Section: Case Studymentioning

confidence: 99%

Peak Load Regulation and Cost Optimization for Microgrids by Installing a Heat Storage Tank and a Portable Energy System

Zhang

Gong

et al. 2018

Applied Sciences

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Abstract:With the rapid growth of electricity demands, many traditional distributed networks cannot cover their peak demands, especially in the evening. Additionally, with the interconnection of distributed electrical and thermal grids, system operational flexibility and energy efficiency can be affected as well. Therefore, by adding a portable energy system and a heat storage tank to the traditional distributed system, this paper proposes a newly defined distributed network to deal with the aforementioned problems. Simulation results show that by adding a portable energy system, fossil fuel energy consumption and daily operation cost can be reduced by 8% and 28.29%, respectively. Moreover, system peak load regulating capacity can be significantly improved. However, by introducing the portable energy system to the grid, system uncertainty can be increased to some extent. Therefore, chance constrained programming is proposed to control the system while considering system uncertainty. By applying Particle Swarm Optimization-Monte Carlo to solve the chance constrained programming, results show that power system economy and uncertainty can be compromised by selecting appropriate confidence levels α and β. It is also reported that by installing an extra heat storage tank, combined heat and power energy efficiency can be significantly improved and the installation capacity of the battery can be reduced.

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“…">IntroductionRenewable energy sources such as wind and photovoltaic power generation have experienced explosive growth, and their natural intermittence brings new challenges for the economic and safe operation of renewable power systems. To handle uncertainties of renewable energy sources [1,2], an effective scheduling method for a multi-energy complementary generation system [3,4] is pressingly needed to alleviate the volatility of renewable power generation [5].At present, there are a few studies for the combined operation of a multiple-source power generation system [6][7][8]. A hybrid scheduling optimization model was proposed in [9] to manage the demand response for cascaded hydropower and wind-photovoltaic power stations.…”

mentioning

confidence: 99%

Multi-Time-Scale Coordinated Operation of a Combined System with Wind-Solar-Thermal-Hydro Power and Battery Units

Zhang¹,

Du²,

Yin³

et al. 2019

Applied Sciences

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The grid connection of intermittent energy sources such as wind power and photovoltaic power generation brings new challenges for the economic and safe operation of renewable power systems. To address these challenges, a multi-time-scale active power coordinated operation method, consisting of day-ahead scheduling, hour-level rolling corrective scheduling, and real-time corrective scheduling, is proposed for the combined operation of wind-photovoltaic-thermal-hydro power and battery (WPTHB) to handle renewable power fluctuations. In day-ahead scheduling, the optimal power outputs of thermal power units, hydro-pumped storage units, and batteries are solved with the purpose of minimizing the total power generation cost. In hour-level rolling corrective scheduling, the power output plan of thermal power units and pumped storage units is modified to minimize the correction cost based on the on-off state of thermal power units determined in day-ahead scheduling. In real-time corrective scheduling stage, the feedback correction and rolling optimization-based model predictive control algorithm is adopted to modify the power output of thermal power units, hydro-pumped storage units, and batteries optimized in hour-level rolling correction scheduling, so as to ensure the economy of the correction plan and the static security of system operation. Finally, simulation results demonstrated that the proposed method can accurately track system power fluctuations, and ensure the economic and security operation of a multi-energy-generation system. IntroductionRenewable energy sources such as wind and photovoltaic power generation have experienced explosive growth, and their natural intermittence brings new challenges for the economic and safe operation of renewable power systems. To handle uncertainties of renewable energy sources [1,2], an effective scheduling method for a multi-energy complementary generation system [3,4] is pressingly needed to alleviate the volatility of renewable power generation [5].At present, there are a few studies for the combined operation of a multiple-source power generation system [6][7][8]. A hybrid scheduling optimization model was proposed in [9] to manage the demand response for cascaded hydropower and wind-photovoltaic power stations. An integrated dispatch model with a multi-objective function was presented in [10] for optimizing the wind-photovoltaic-storage power generation output under generalized load fluctuations. In [11], a wind-hydro-thermal unit combination model was established for a day-ahead scheduling plan, and afterward the model was solved by variables separation and a piecewise linear strategy to manage the hydraulic production capacity curve. An optimal operation model for a large-scale

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Optimal economic dispatch of FC-CHP based heat and power micro-grids

Cited by 216 publications

References 40 publications

New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power

New optimization method based on energy management in microgrids based on energy storage systems and combined heat and power

Peak Load Regulation and Cost Optimization for Microgrids by Installing a Heat Storage Tank and a Portable Energy System

Multi-Time-Scale Coordinated Operation of a Combined System with Wind-Solar-Thermal-Hydro Power and Battery Units

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