Optimal performance of CCHP based microgrid considering environmental issue in the presence of real time demand response

Saberi, Kasra; Pashaei-Didani, Hamed; Nourollahi, Ramin; Zare, Kazem; Nojavan, Sayyad

doi:10.1016/j.scs.2018.12.023

Cited by 89 publications

(33 citation statements)

References 30 publications

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“…A two-stage planning technique has been developed in [17], to minimize the annual capital cost and the EOC of the multi-CCHP-based microgrids. A CCHPbased system considering the RTP_DRP has been studied in [18], to minimize the EOC and the emitted CO2 at the same time. A multi-objective planning model has been provided in [19] to analyze the renewable energy sourcebased CCHP model, considering its economic and environmental constraints.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…(8)-(10) are provided to calculate the outputs of the WT, PS, and STS [38][39][40][41]. (19) and (20) are provided to model the charge/discharge process in the ESS [18,38]. It is noteworthy that the studied model is optimized in a short-term framework, and constraints used to model the lifecycles of the ESS are not considered in this paper.…”

Section: Wt Ps and Sts Constraintsmentioning

confidence: 99%

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Environmental and Economic Operation of Wind-PV-CCHP-Based Energy System Considering Risk Analysis Via Downside Risk Constraints Technique

et al. 2020

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Combined Cooling, Heating, and Electrical (CCHP)-based microgrids meet various energy demands at the same time. Risk analysis of such CCHP-based microgrids under environmental and economic constraints is a challenging issue. Furthermore, high penetration of various renewable energy sources in such CCHP-based microgrids clouds the issue. Thus, Downside risk constraints technique (DRCT) is employed in this paper to manage and minimize the risk associated with various uncertainties in the studied sample CCHP-based microgrid under environmental and economic constraints. The uncertainties of solar radiation, wind speed, market tariff and cooling, heating, and electrical demands are considered, and the stochastic optimization approach is used to model the mentioned uncertainties. The effect of the Real-Time Pricing rate of the Demand Response Program (RTP-DRP) has been studied in this paper. By analyzing the obtained results, it can be found that with considering DRCT, the risk-in-cost (RC) level can plunge to 0 respectively by paying 2.61% and 1.68% without and with RTP-DRP.

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Section: A Literature Reviewmentioning

confidence: 99%

Section: Wt Ps and Sts Constraintsmentioning

confidence: 99%

Environmental and Economic Operation of Wind-PV-CCHP-Based Energy System Considering Risk Analysis Via Downside Risk Constraints Technique

et al. 2020

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“…References [9], [10] further subdivided the regional energy supply and demand relationships into three busbars (the electricity, cold and heat busbars) to establish a more refined multi-energy supply structure and proposed an optimal operation method for the established multi-energy system. In the presence of real time demand response guided by energy price, [11] proposed a multi-objective RIES scheduling model that includes reducing carbon emission and operation cost. References [12], [13] established models for interruptible loads of electrical and thermal power.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling Method for a Regional Integrated Energy System Considering Joint Virtual Energy Storage

et al. 2019

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Energy storage equipment is an important part of integrated energy systems, but the construction and operational costs of it are great. Therefore, it's difficult to apply energy storage equipment on a large scale. As an alternative measure, adjusting controllable loads including electric vehicles (EVs) and air conditioning loads jointly can transfer loads across time periods and reduce variation difference between heat and electric loads. These controllable loads can be regarded as ''virtual energy storage system''. Managing the charging of EVs and heat storage of buildings, a joint virtual energy storage system including electric energy storage and thermal energy storage is proposed in this paper. Then, these models are integrated into a scheduling model for regional integrated energy system (RIES). The charging/discharging power management of joint virtual energy storage systems can be realized by arranging the charging of EVs based on vehicle-driven rules and by adjusting building indoor temperatures within the temperature comfort range. Finally, simulations are carried out to demonstrate the effectiveness of the scheduling method. Simulation results show that the RIES optimal scheduling model considering joint virtual energy storage can reduce operational costs. The stability of RIES is improved with the combination of virtual electrical and thermal energy storage. INDEX TERMS Virtual energy storage, regional integrated energy system, economic dispatching, heat storage capability of building, ordered charging of electric vehicles. LEI CHEN (M'12) was born in Jingzhou, China, in 1982. He received the B.S. and Ph.D. degrees in electrical engineering from the School of Electrical and Electronic Engineering, Huazhong Uni

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“…An improved energy hub system combined with cooling, heating, and power integrated with photovoltaic and wind turbine, demonstrated that operation cost and carbon emission were reduced by 3.9% and 2.26%, respectively [16]. In Canada a battery storage system to minimize the energy drawn from the public grid was proposed This storage system was charged from wind turbines and the energy stores were discharged to a park when the wind park power dropped below 0 kW and the storage system was able to offset 17.2 MWh but the financial gain was insufficient to offset the net energy losses in the storage system [17].…”

Section: Introductionmentioning

confidence: 99%

Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico

et al. 2019

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The Energetic Transition Law in Mexico has established that in the next years, the country has to produce at least 35% of its energy from clean sources in 2024. Based on this, a proposal in this study is the cogeneration between the principal thermal power plants along the Mexican states of the Gulf of Mexico with modeled wind farms near to these thermal plants with the objective to reduce peak electricity demand. These microscale models were done with hourly MERRA-2 data that included wind speed, wind direction, temperature, and atmospheric pressure with records from 1980–2018 and taking into account roughness, orography, and climatology of the site. Wind speed daily profile for each model was compared to electricity demand trajectory, and it was seen that wind speed has a peak at the same time. The amount of power delivered to the electric grid with this cogeneration in Rio Bravo and Altamira (Northeast region) is 2657.02 MW and for Tuxpan and Dos Bocas from the Eastern region is 3196.18 MW. This implies a reduction at the peak demand. In the Northeast region, the power demand at the peak is 8000 MW, and for Eastern region 7200 MW. If wind farms and thermal power plants work at the same time in Northeast and Eastern regions, the amount of power delivered by other sources of energy at this moment will be 5342.98 MW and 4003.82 MW, respectively.

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Optimal performance of CCHP based microgrid considering environmental issue in the presence of real time demand response

Cited by 89 publications

References 30 publications

Environmental and Economic Operation of Wind-PV-CCHP-Based Energy System Considering Risk Analysis Via Downside Risk Constraints Technique

Environmental and Economic Operation of Wind-PV-CCHP-Based Energy System Considering Risk Analysis Via Downside Risk Constraints Technique

Optimal Scheduling Method for a Regional Integrated Energy System Considering Joint Virtual Energy Storage

Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico

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