Analysis and optimization of CCHP systems based on energy, economical, and environmental considerations

Mago, Pedro J.; Chamra, Louay M.

doi:10.1016/j.enbuild.2009.05.014

Cited by 330 publications

(135 citation statements)

References 16 publications

Supporting

Mentioning

132

Contrasting

Unclassified

Order By: Relevance

“…The thermal energy storage (TES) is a flexible component of the plant, which allows the campus to reshape the cooling demand particularly in peak hours. There are many examples of CCHP supervisory control systems in literature [5,6,10]. A key element for such optimal control is to have accurate information about the power (electricity and cooling) demand over the course of a day, which is the central focus of this study.…”

Section: Case Study and Experimentationmentioning

confidence: 99%

“…The cooling and electricity load demands are outputs of running the simulation and are then fed into the optimization model [10][11][12]. However, the quality of results highly depends on quality of the simulation models and their inputs.…”

Section: Introductionmentioning

confidence: 99%

“…A wide range of optimal control strategies has been proposed to improve the CCHP operation based on different objectives including power flow, capacity, operation, energy-use and environmental considerations [5][6][7][8][9][10][11][12]. A common element in almost all optimal control strategies is to have an accurate estimation of cooling, heating, and electricity load demands.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modeling and forecasting of cooling and electricity load demand

et al. 2014

View full text Add to dashboard Cite

h i g h l i g h t sWe propose a model for forecasting cooling and electricity load demand. The model takes the advantage of both time series and regression methods. The model is able to accurately forecast the load demands of the CCHP system. a r t i c l e i n f o t r a c tThe objective of this paper is to extend a statistical approach to effectively provide look-ahead forecasts for cooling and electricity demand load. Our proposed model is a generalized form of a Cochrane-Orcutt estimation technique that combines a multiple linear regression model and a seasonal autoregressive moving average model. The proposed model is adaptive so that it updates forecast values every time that new information on cooling and electricity load is received. Therefore, the model can simultaneously take advantage of two statistical methods, time series, and linear regression in an adaptive way. The effectiveness of the proposed forecast model is shown through a use case. The example utilizes the proposed approach for economic dispatching of a combined cooling, heating and power (CCHP) plant at the University of California, Irvine. The results reveal the effectiveness of the proposed forecast model.

show abstract

Section: Case Study and Experimentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling and forecasting of cooling and electricity load demand

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Cost on coal, such as mining cost, environment expenses and investment on physical distribution will present as part of cost of electricity generation and will be paid by the power plant. Such cost can be minimised by independently optimising the electricity quota while maintaining total quantity of electricity generated and satisfying the constriction in the grid [10].…”

Section: The Goal Of Minimising the Cost Of Electricity Generationmentioning

confidence: 99%

The Researching Mode Based on Generating Self-optimization of Global Optimization

Zou¹,

Hu²,

Zhigong³

et al. 2015

TOPEJ

View full text Add to dashboard Cite

A method of global optimizing power generation is introduced in this paper. Under the condition of maintaining the same working hours of different units, electricity quantity generated between the different power suppliers is equal in one province, and it is also fulfilling the primary electricity schedule with a secure stable power system and low emission. This method is capable of minimizing resource consumption and emission while satisfying the power requirement by independently adjusting electricity generating units internally to optimum. Therefore, it is an important and effective way to promote energy saving in power generating and controlling.

show abstract

“…3). Simultaneously, the working conditions and effectiveness of chilled water production by absorption chillers are improved [9][10][11]. Fig.…”

Section: Operational Analyses Of Dhs Due To Introduction Of Cooling Gmentioning

confidence: 99%

Analysis of a combined heating and cooling system model under different operating strategies

Dzierzgowski

Zwierzchowski

2017

E3S Web Conf.

View full text Add to dashboard Cite

Abstract. The paper presents an analysis of a combined heating and cooling system model under different operating strategies. Cooling demand for air conditioning purposes has grown steadily in Poland since the early 1990s. The main clients are large office buildings and shopping malls in downtown locations. Increased demand for heat in the summer would mitigate a number of problems regarding District Heating System (DHS) operation at minimum power, affecting the average annual price of heat (in summertime the share of costs related to transport losses is a strong cost factor). In the paper, computer simulations were performed for different supply network water temperature, assuming as input, real changes in the parameters of the DHS (heat demand, flow rates, etc.). On the basis of calculations and taking into account investment costs of the Absorption Refrigeration System (ARS) and the Thermal Energy Storage (TES) system, an optimal capacity of the TES system was proposed to ensure smooth and efficient operation of the District Heating Plant (DHP). Application of ARS with the TES system in the DHS in question increases net profit by 19.4%, reducing the cooling price for consumers by 40%.

show abstract

Analysis and optimization of CCHP systems based on energy, economical, and environmental considerations

Cited by 330 publications

References 16 publications

Modeling and forecasting of cooling and electricity load demand

Modeling and forecasting of cooling and electricity load demand

The Researching Mode Based on Generating Self-optimization of Global Optimization

Analysis of a combined heating and cooling system model under different operating strategies

Contact Info

Product

Resources

About