Renewable Energy Global Innovations features: Optimal Design of Modular Cogeneration Plants for Hospital Facilities and Robustness Evaluation of the Results

Significance Statement

A cogeneration technique such as the combined heat and power generation offers prospects for emission of non-toxic gases which are in serious need for the energy demand world. Hence several research efforts have been conducted to obtain a desirable balance between energy supply and economic objectives.

Researchers from University of Naples Federico II in Italy proposed a new methodology which involves a coupled calculation algorithm to genetic optimization algorithm MOGA II and a multi-objective robust design optimization approach in order to determine the capabilities of an optimized combined heat and power plants in hospital facilities. The research work is now published in Energy Conversion and Management.

The calculation algorithm developed to the genetic optimization algorithm compares the specific load profiles of two Italian hospital facilities while considering the combined heat and power system-user interaction with the sole objective of increasing the total primary energy conversion and reducing the simple payback period. The multi-objective optimization approach which also involves robust design optimization involved a sensitivity analysis which accommodates certain uncertainties economic-wise and energy as well.

The authors implemented two management strategies in the calculation algorithm; maximum primary energy savings management MPESM logic and maximum profitability management MPM logic. They investigated load profiles of the two hospital facilities were the S. Paolo hospital in Naples and the second, Oncological Reference Center of Basilicata CROB.

Pareto optimal front solutions derived from the multi-objective optimization approach when using the MPSEM strategy in a hospital facility of S. Paolo showed that plant configurations which aid the overall energy savings favors the simple payback period. A multiple gas engine of two and three, gave an optimum relation between the energy and economic results. A reasonable Pareto optimal front solutions were observed in the total primary energy savings at a value greater than 16.5%, the simple payback period between 2.9- 4.6 years and engines between one to three with an electrical power range between 260-570KW for each. The MPM logic had a decreased efficiency in designing an optimized plant configuration.

The Pareto optimal front solutions when considering a hospital facility of CROB indicated a higher value of total primary energy savings at 18.2%, while the simple payback period is a little above 3 years with three combined heat and power engines of 440KW. With the use of MPM logic strategy, a decrease in total primary energy savings of 0.5% was discovered. Compared to that of S. Paolo hospital facility, that of CROB had a higher total primary savings value in all cases.

Results from the Pareto optimal solutions for the first multi-objective optimization approach used in the S. Paolo hospital indicated a higher economic sensitivity compared to the energetic sensitivity as standard deviation accounted up to 7% of its mean value ratios under 3% for total primary energy savings. The most stable plant design for the two hospital facilities was also provided.

However, the multi-objective robust design optimization in order to derive a last-longing solution economically and energetically, gave Pareto optimal solutions with standard deviation for a simple payback period less than 3.5% of its mean value, which reaches 7% of the total primary savings in hospital facility of S. Paolo. Pareto optimal solutions for the hospital facility in the CROB had a standard deviation of simple payback less than 2.5% of its mean value while reaching 6% of the total primary energy savings.

The optimization tool proposed in this study provides a reasonable approach for determining long-lasting performance for the combined heat and power plant while considering its effect on the economy and energy supply.

About The Author

Massimiliano Muccillo received his degree in Mechanical Engineering at the University of Naples Federico II, Italy, in 2008, discussing a thesis addressing the study of the prototype of a variable valve actuation system for a motorcycle engine. He received his Ph.D degree in Engineering of Mechanical Systems at the University of Naples Federico II, in 2012, discussing a thesis addressing the use of the multi-objective approach for the optimization of cogeneration systems. Since 2012, he has been a Research fellow at the Department of Industrial Engineering of the University of Naples Federico II.

His research interests include modeling, analysis and optimization of spark ignition reciprocating internal combustion, CHP systems and ORC systems. SAE member since 2012. ATI member since 2012. Author of about 25 scientific publications (13 SCOPUS). “Key Scientific Article contributing to the excellence in Energy research” by RENEWABLE ENERGY GLOBAL INNOVATIONS (http://ift.tt/2ndOosK) in 2014.

About The Author

Alfredo Gimelli associate Professor of Fluid Machines and Energy Systems at the Department of industrial Engineering of the University of Napoli Federico II (Italy). Scientific Council Member of the Industrial Engineering doctoral since 2012. Scientific Council Member of the Mechanical Engineering doctoral since 2008. Research interests are related to: – Internal Combustion Engines: Experiments and Modeling;- Energy Efficiency; – Renewable Energy: Biomass, CSP Thermodynamic Cycles and Syngas from Waste; – Combined Heat and Power; – Multi Objective Optimization; – ORC Power Plants. Graduated with honors in Mechanical Engineering at the University of Napoli (Italy) in 1994. Philosophic Doctor in Mechanical Engineering in 1999. SAE member since 2003. ATI member since 1997.

Author of more than 70 scientific publications (40 SCOPUS – 15 ISI journals) and 1 European Patent. ACA Noise&Vibration Award in 2005. “Key Scientific Article contributing to the excellence in Energy research” by RENEWABLE ENERGY GLOBAL INNOVATIONS (http://ift.tt/2ndOosK) in 2014. Scientific responsible of more than 10 research programs/projects/contracts. Creator and founder of a high-tech company in the renewable and energy saving technologies.

Reference

Gimelli, A., Muccillo, M., Sannino, R. Optimal Design of Modular Cogeneration Plants for Hospital Facilities and Robustness Evaluation of the Results, Energy Conversion and Management 134 (2017) 20–31.

DII – Department of Industrial Engineering, University of Naples Federico II, Via Claudio 21, 80125 Napoli, Italy.

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Renewable Energy Global Innovations features: Steam Reforming of n-dodecane over K2Ti2O5-added Ni-Alumina and Ni-Zirconia (YSZ) catalysts

Significance Statement

Diesel is known to contain high presence of hydrogen, which makes them a favorite source for catalytic conversion process of fuel. Hydrogen, which provides clean energy to the environment, is often produced through the catalytic conversion form of steam reforming process due to its high optimality and selectivity towards hydrogen.

The catalyst majorly used in a catalytic conversion of fuels to hydrogen in the steam reforming process, is nickel-based with other supporting materials such as alumina and yttrium-stabilized zirconia. However, deposition of carbon on catalyst during the steam reforming process limits the efficiency of the nickel supported catalyst. This as a result led to the introduction of second catalytic material such as K₂Ti₂O₅ which has high thermal stability and ability to oxidize the carbon deposits at the same time.

Researchers led by Professor Jong Shik Chung from Pohang University of Science and Technology in Republic of Korea investigated the addition of  K₂Ti₂O₅ particles on nickel supported on alumina Ni-Al₂O₃ and yttrium-stabilized zirconia Ni-YSZ catalyst in the steam reforming reaction of n-dodecane. The research work is now published in peer-reviewed journal, International Journal of Hydrogen Energy.

The authors investigated the performance of the added K₂Ti₂O₅ on nickel-based supported catalyst with the use of Brunauer-Emmett-Teller analysis, x-ray diffraction, thermogravimetric analysis, transmission electron microscopy and electron energy loss spectrometer coupled with their total selectivity towards hydrogen, carbon monoxide, carbon dioxide and methane.

At gas hourly space velocity of 15000h^-1, the yttrium-stabilized zirconia supports on the nickel catalyst possessed more selectivity towards hydrogen and other gases compared to other alumina supported catalyst. However, the addition of K₂Ti₂O₅ particles on the nickel supports on yttrium-stabilized zirconia catalyst maintained the conversion process without a decrease in its activities compared to others.

The decreased activity of K₂Ti₂O₅ particles on the nickel supported on alumina catalyst was due to the low contact between the nickel particles and K₂Ti₂O₅ phase as a result of the hindered presence of nickel particles in the alumina pores. This was a different case for that of yttrium-stabilized zirconia catalyst as nickel particles were found in the zirconia supports, aiding good contact.

At high gas hourly space velocity below 20000h^-1, the addition of K₂Ti₂O₅ particles on the nickel-supported yttrium-stabilized zirconia catalyst maintained good stability due to the oxidation of deposited carbon on the surface of the catalyst.  The addition of K₂Ti₂O₅ particles on the nickel-supported yttrium-stabilized zirconia catalyst also aided the non-existence of hard carbons except at gas hourly space velocity of 30000h^-1.

Results from transmission electron microscopy and electron energy loss spectroscopy the authors indicated that both the present and absent K₂Ti₂O₅ particles on the nickel-based yttrium-stabilized zirconia catalyst were effective in selectivity of hydrogen at a gas hourly space velocity of 5000h^-1. The absence and presence of K₂Ti₂O₅ particles on the nickel-based yttrium-stabilized zirconia catalyst deactivates at gas hourly space velocity of 5000h^-1 and 20000h^-1 respectively.

This study was able to provide an absolute range of effectiveness of the added K₂Ti₂O₅ on yttrium-stabilized zirconia catalyst for the steam reforming process of n-dodecane.    

About The Author

Dr. Taewook Kim is a postdoctoral and assistant researcher in the Department of Chemical Engineering at Pohang University of Science and Technology (POSTECH), Korea. He received Ph.D. degree at the same university (POSTECH) in 2017. His research areas are Reforming Catalysts of Hydrocarbon and Solid Oxide Fuel Cells.

About The Author

Dr. Jong-Shik Chung is a professor in the Department of Chemical Engineering and a head of Institute of New and Renewable Energy at Pohang University of Science and Technology (POSTECH), Korea. His research areas are Solid Oxide Fuel Cells (Materials, Stacks, and System), Reforming Catalysts and Reformers, Desulfurization, and Waste water treatments.

Journal Reference

Kim, T., Song, K.H., Yoon, H., Chung, J.S. Steam Reforming of n-dodecane over K₂Ti₂O₅-added Ni-alumina and Ni-zirconia (YSZ) Catalysts, International Journal of Hydrogen Energy 41 (2016) 17922-17932.

Department of Chemical Engineering, Pohang University of Science and Technology (POSTECH), 77 Cheongam-Ro, Pohang, 37673, Republic of Korea.

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Renewable Energy Global Innovations features: Decision Framework for Feasibility Analysis of Introducing the Steam Turbine Unit to Recover Industrial Waste Heat Based on Economic and Environmental Assessment

Significance Statement

Various technologies involved in reduction of carbon emissions have been implemented in order to provide an equal source of energy supply and in essence, produce gases which are non-toxic to the environment. In view of advancing energy efficiency, recovery of heat energy from industrial waste which can be classified as a source of renewable energy can certainly satisfy both economic and environmental benefits.

A steam turbine unit can efficiently serve as one of the techniques used for waste heat recovery. However, little or no assessment has been made in essence, of providing a decision framework to test its economic and environmental impacts.

Wujie Zhang and colleagues from Zhejiang University in China provided a decision framework for initiating a feasible criterion by simply undergoing an economic and environmental assessment of an industrial waste heat recovery from a steam turbine unit. The research is now published in Journal of Cleaner Production.

Two working modes of the steam turbine unit were considered as a result of their energy output; electrical and mechanical driving force. After certain assumptions, the authors established economic and environmental models which were based on cost-benefit analysis and life-cycle assessment in order to ascertain the benefits of waste heat recovery from the steam turbine unit according to their respective working modes.

The decision framework incorporates three possible outcomes each for both economic benefit and environmental impact of the steam turbine unit. Nine possible combinations were also provided by the cost-benefit analysis and life-cycle assessment results in order to maximize the economic and environmental benefits of the steam turbine unit. Further analysis, however, indicated that the working mode based on the mechanical driving force showed more environmental benefits, but the economic profits remained the same for the two working modes.

The derived decision framework when utilized in a case study of a petrochemical plant, producing terephthalic acid in China, observed a payback period of 2.28 years with energy conservation as high as 2 x 10⁵ GJ for an approximate payback period of 0.12 years. This result shows that the decision framework provided by the way of the authors, can efficiently assess the environmental and economic benefits of an industrial waste heat recovery system.

With the aid of decision framework, in view of providing feasibility analysis on a waste heat recovery technique, the authors were able to show that the steam turbine unit not only conforms to a renewable energy source, but also provides both economic and environmental benefits to consumers.

Journal Reference

W. Zhang^1,2, F. Gu³, F. Dai^1,2, X. Gu^1,2, F. Yue^1,2, B. Bao^1,2, Decision Framework for Feasibility Analysis of Introducing the Steam Turbine Unit to Recover Industrial Waste Heat Based on Economic and Environmental Assessment, Journal of Cleaner Production 137 (2016) 1491-1502.

Show Affiliations

1. Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, College of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China.
2. The State Key Laboratory of Fluid Power Transmission and Control, College of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China.
3. Faculty of Science and Engineering, University of Nottingham, Ningbo, 315100, China.

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Renewable Energy Global Innovations features: Hydrothermal Synthesis of Manganese Oxide Encapsulated Multiporous Carbon Nanofibers for Supercapacitors

Significance Statement

Hydrothermal carbonization is a newly developed technique used in generating carbon nanofibers. Despite its many advantages have certain challenges due to its undesired surface morphology and singly resultant production of microporous carbon. A better use of the hydrothermal carbonization technique in fabricating multiporous carbon nanofibers with the encapsulation of certain metal oxides is of relevance to areas where supercapacitors, in view of energy storage application is needed. Hence, various methods need to be implemented in improving the hydrothermal carbonization technique in order to achieve this feat.

Researchers led by Professor Yong Wang from Zhejiang University in China developed a new dopamine-assisted hydrothermal carbonization technique to fabricate manganese oxide encapsulated multiporous carbon nanofibers M-MCNFs from glucose. The research work is now published in peer-reviewed journal, Nano Research.

With the addition of cryptomelane nanowires, the authors were able to verify the importance of dopamine addition, as it supported the formation of carbon nanofibers. The manganese oxide encapsulated multiporous carbon nanofibers structures contained hierarchical pore structures such as macropores, mesopores and micropores.

The presence of dopamine, which was responsible for the quick formation of carbon nanofibers also aided the cryptomelane hard-templates of manganese oxide nanowires and glucose reaction. The presence of F127 aided the discovery of mesoporous structures with higher specific surface area and volume for manganese oxide encapsulated multiporous carbon nanofibers compared with the manganese oxide carbon nanofibers.

Further results also highlighted the reduction of the cryptomelane hard-template of manganese oxide to nanowires of Mn₃O₄ nanoparticles after high-temperature  annealing. The presence of Mn₃O₄ favored the capacitive performance of the manganese oxide encapsulated multiporous carbon nanofibers as the active redox sites were enhanced by the multipores which prevents the introduction of post disposition procedure.

The structural properties with large surface areas and hierarchical pores (macropores, mesopores and micropores) made the manganese oxide encapsulated multipores carbon nanofibers a far better choice for applications of supercapacitors.

From electrochemical measurements, the authors were able to show that manganese oxide encapsulated carbon nanofibers possess a favorable charge-discharge properties as well as high cycle stability and high capacity retention when tested under different electrolytes.

The method used in fabricating the manganese oxide encapsulated multiporous carbon nanofibers by the way of the authors creates an avenue for improved energy storage applications with the use of renewable source such as biomass. The strategy also pave a way to synthesize porous carbon nanofibers from biomass.

About The Author

Yong Wang studied chemical engineering at Xiang-tan University from 1998 to 2002. He received his Ph.D. degree from Zhejiang University in 2007. After a postdoctoral stay at the Department of Chemistry, Zhejiang University, he joined the Max Planck Institute for Colloids and Interfaces in Potsdam/Germany in 2009. He rejoined Zhejiang University and became a Professor for Chemistry in 2011. His research focuses on design and synthesis of novel materials for energy conversion and storage, heterogeneous catalysis and biomass conversion.

About The Author

Haiyan Wang is a Ph.D. candidate in the Advanced Materials and Catalysis Group at Zhejiang University under the direction of Prof. Yong Wang. She received her Bachelor’s degree from Henan Normal University in 2013. Her research interests are synthesis of carbon-based nanomaterials and their applications in electrochemical energy storage and conversion devices.

Journal Reference

Wang, H., Deng, J., Chen, Y., Xu, F., Wei, Z., Wang, Y. Hydrothermal Synthesis of Manganese Oxide Encapsulated Multiporous Carbon Nanofibers for Supercapacitors, Nano Research 9 (2016) 2672-2680.

Advanced Materials and Catalysis Group, ZJU-NHU United R&D Center, Center for Chemistry of High-Performance and Novel Materials, Department of Chemistry, Zhejiang University, Hangzhou, China.

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Renewable Energy Global Innovations features: Reformulation of parameters of the logistic function applied to power curves of wind turbines

Significance Statement

The power curve of a wind turbine indicates the relationship between the wind speed and the electric power supplied. Therefore, it is widely used when analyzing or studying a wind turbine or a wind farm. The power curve of a wind turbine is the one provided in the manufacturer’s paperwork. This paper will focus on the modeling of this curve although measurements in the wind turbine in a wind farm will eventually reveal conditions that can slightly differ from those stated by the manufacturer. There are circumstances that can affect the operating conditions, and they include, turbulence, gusty winds, wind shear, wake effects, icing and component fatigue in the wind turbine.

Daniel Villanueva and Andrés Feijóo from de Vigo university in Spain proposed a method that would lead to the reformulation of parameters of the logistic function applied to power curves of wind turbines. They presented an alternative procedure to obtain parameters of the 4-parameter logistic function in order to improve the model. Their work is now published in peer-reviewed journal, Electric Power Systems Research.

The models used were based on the 4-parameter logistic function model, where the relationship between wind speed and generated power is a continuous curve. The parameters of the model obtained by using optimization techniques have no technical meaning. In order to know the influence of the wind turbine’s features and behaviors, another model is needed. The reason behind using parameters with some technical meaning is in order to assess the power curve from a theoretical point of view and obtain the weight of each parameter in the power curve and in the power output.

The method adopted in this paper consists of obtaining the parameters of the model from the features of a wind turbine power curve. Each feature investigated imposes a constraint that must be satisfied by the model, and this contributes to the configuration of the end result. Therefore, a deterministic process is proposed to obtain the parameters of the 4-parameter logistic model, which are obtained directly from the features of the power curve.

Three wind turbine power curve models based on a reformulation of the parameters of the logistic curve function were presented. The first one 4P-DP is similar to the 4-parameter logistic function but takes into account a deterministic procedure to obtain its parameters making the model meaningful since it provides information on the wind turbine behavior.

The second model (4P-DS), obtained by the means of simplification, some issues were improved, for instance, approximations to the power curve lower values of wind speed and ease of obtaining probability density function (PDF) expressions. The models consist of a continuous function that simplified the implementation of the curve in a computer program compared to the piecewise models.

The third one (3P-DP) simplifies even more the former expression and provides an easy way to model the power curve with just three parameters.

One result that can be obtained from these models is the expression of the PDF of the output power. This will provide a cumulative behavior of the power and can be used as input data to solve more complex problems such as probabilistic load flow, where the probabilistic behavior of the power is taken into consideration.

In order to check the proposed models, several wind turbines were taken into account. This was in a bid to make detailed comparison of wind turbines of the same rated power from difference manufacturers, and to check models for a wide range of rated powers.

About The Author

Daniel Villanueva joined the Departamento de Enxeñería Eléctrica of the Universidade de Vigo, Spain, in 2009, obtaining a PhD built on the analysis of the correlation among neighboring wind speeds and its joint impact in the electrical networks. As a consequence, he has co-developed several mathematical/technical tools, as the following: analysis of the wind speed behaviour, simulation of correlated non-Normal series of data, different wind power curve models, expressions for the wind power Probability Density Function, analysis of Probabilistic Load Flow with wind power, simulation of wind speed data for Economic Dispatch assessment, etc.

About The Author

Andrés Elías Feijóo Lorenzo received his MsC in electrical engineering from the Universidade de Santiago de Compostela, Spain, in 1990. After this, he obtained a PhD degree in electrical engineering from the Universidade de Vigo, Spain, with a thesis about the influence of wind farms in steady-state security assessment and power quality of large electrical power networks.

He is now with the Departamento de Enxeñería Eléctrica of this university and his field of research is wind energy, in particular steady-state and dynamic models of wind turbines, and simulation of wind turbines and wind farms including the analysis of the behavior of wind speed. All mathematical tools for the approach to these problems are of interest.

Reference

Daniel Villanueva, Andrés E. Feijóo. Reformulation of parameters of the logistic function applied to power curves of wind turbines. Electric Power Systems Research, volume 137 (2016), pages 51–58.

Departamento de Enxeñería Eléctrica, Universidade de Vigo, EEI, Campus de Lagoas-Marcosende, 36310 Vigo, Spain.

 

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Renewable Energy Global Innovations features: Photovoltaic energy systems with battery storage for residential areas: an economic analysis

Significance Statement

Photovoltaic energy finds its application in various fields like agriculture, industry, telecommunication, etc. In the global energy market, photovoltaic energy helps in creating a sustainable development. Various methods have been adopted to decrease the emission of greenhouse gases into the atmosphere. To decrease the global temperature level, burning of fossil fuels should be eliminated. Renewable sources of energy are used as an alternative to fossil fuels. The demand for energy and its consumption is increasing every year.

A group of researchers from the University of L’Aquila in Italy considered a residential sector where they evaluated the profitability of mono-crystalline photovoltaic systems, without any subsidies. They also evaluated the profitability of lead acid energy storage system. Based on discounted cash flows, a quantitative analysis is proposed with a sensitivity analysis of the photovoltaic system; its investment cost, electricity purchase and sale prices, insolation levels, battery storage capacities was also conducted.

The authors performed a case study which showed that the installed power and the electrical generation increased every year. To reduce the emission of carbon dioxide, two parameters were considered; one is the emissions released by a national energy mix and the other is the emissions released by the photovoltaic system. To increase self-consumption, the energy storage system is considered.

Photovoltaic system saves energy through internal consumption. The investment cost is high for implementing the system. But, the operation and the maintenance cost are low due to free solar radiation. There are several factors through which the energy output of the photovoltaic system depends. The factors include the insolation rate, the efficiency of balance of system, the installed photovoltaic modules and the nominal power of the modules.

An efficiency reduction factor is considered for the photovoltaic system. The profit obtained from the energy storage system is obtained by saving energy through internal consumption. Photovoltaic systems play a major role in environmental protection and also serve as an economic opportunity. The performance is improved by increasing self-consumption. In sunny areas, photovoltaic systems produce high amount of energy and hence the potential revenue in southern regions are more than the northern regions.

Harmonization between the consumption and production of energy is achieved by using the energy in periods of solar productivity or by using intelligent machinery. A set of input variable is assumed and the net present value is taken. A sensitivity analysis is implemented on the critical variables. By implementing a battery in the photovoltaic system, the intermittence of energy can be resolved. The stability of the applications is thus achieved. The size of the battery and its capacity to store energy need to be considered based on the applications and the demand for energy.

From the proposed mathematical model, the authors defined the breakeven point at which the photovoltaic battery system becomes economically feasible (see figure 1). Static and dynamic scenarios is proposed for the uncertainty that adversely affect the decision making process. Photovoltaic sector plays a strategic role in energy economics. This source is being developed in major countries for clean energy production.

About The Author

Federica Cucchiella is an Associate Professor of Managerial Engineering in the Department of Industrial and Information Engineering & Economics, University of L’Aquila. In this University she teaches Managerial Economy. Her principal area of research regards supply chain management, real option and green supply chain. The results of her researchers are published on relevant international journals, book chapter and referred conference proceedings.

She has participated in several research projects on natural resources and supply chain management. She has organized a number of international and national conferences mainly in the field of supply chain and green supply chain management. She has received scholarships and prizes for academic excellence from various academic institutions and foundations.

She is a member of Editorial board of International Journal of Logistics Economics and Globalisation by Emerald. She is author of more than 60 papers published on refereed books, journals and conference proceedings.

About The Author

Idiano D’Adamo was born in Vasto (Italy) in 1983. In 2008, he received the Master of Science in Management Engineering title. In 2012, he received the PhD in Electrical and Information Engineering. Both these titles were received from the University of L’Aquila. He worked in the University of Sheffield, the National Research Council of Italy and Politecnico di Milano. Currently, he is a postdoctoral researcher at the University of L’Aquila. In August 2015, he published a paper in Renewable and Sustainable Energy Reviews that was awarded with the Elsevier Atlas price. During its academic career, Idiano D’Adamo published 36 papers (publicly available in the Scopus database), receiving 501 citations and reaching an h-index of 14.His current research interests are sustainability, renewable energies management and waste management.

About The Author

Massimo Gastaldi is an Associate Professor in Managerial Engineering at University of L’Aquila since 1998 at Department of Industrial and Information Engineering and Economics where he teaches Applied Economics in Engineering Science and Analysis of Financial Systems. Since 1991 he has contributed with several publications and edited books working for National Research Council (C.N.R.) and at University of Rome “Tor Vergata”. In 1995 he was visiting professor at the California State University, San Marcos, USA and in 1997 at Colorado University, Builder, USA.

Current research issues: regulation and public utilities, green supply chain management, renewable energy and real options, financial analysis. He was responsible manager of private and public research projects. He is editor in chief of the International Journal of Management and Network Economics published by Inderscience. He is author of more than 130 papers published on refereed books, journals and conference proceedings.

Journal Reference

Federica Cucchiella, Idiano D’Adamo, Massimo Gastaldi, Photovoltaic energy systems with battery storage for residential areas: an economic analysis, Journal of Cleaner Production, Volume 131, 2016, Pages 460–474.

Department of Industrial and Information Engineering and Economics, University of L’Aquila, Via G. Gronchi 18, 67100 L’Aquila, Italy.

 

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Renewable Energy Global Innovations features: Robust Environmental-Economic Dispatch Incorporating Wind Power Generation and Carbon Capture Plants

Significance Statement

Due to the proliferation of renewable power generation and the adoption of carbon capture technologies aiming to reduce carbon dioxide emissions and alleviate environmental pollution, various uncertainties accompany the use of environmental-economic dispatch method. A two-stage robust optimization framework affords one of the best approaches used for coping with these uncertain factors. However, this approach has handiest been applied in optimization problems with sole objective. As a way of providing the most desirable and efficient control of carbon emissions, high generation cost as a result of energy consumption in carbon capture plants needs to be considered also.

A group of researchers led by Dr. Wei Wei from Tsinghua University and in collaboration with Dr. Jianhui Wang from Argonne National Laboratory in USA and professor Tiejiang Yuan from Xinjiang University in China proposed a robust environmental-economic dispatch method which provides both energy optimization and reverse scheduling while considering the operation of carbon capture plants and volatility of large-scale wind power generation. Additionally, they made use of a Nash bargaining criterion to strike a balance between generation cost and carbon emission without a clear carbon tax or emission cap for building a single-objective optimization model with clear physical meaning. The research work is now published in the journal, Applied Energy.

The authors devised a non-parametric scalarization model for the environmental-economic dispatch problem, which is shown to be equivalent to a second-order cone program, and suggested an adaptive scenario generation algorithm to solve the robust model in a tractable manner. The computations of the Pareto front could be achieved by using the ɛ-constraint method since both of the objectives under investigation are convex functions.

With the provision of the formulated environmental-economic dispatch model incorporating carbon capture plants and volatile wind generation, PJM 5-bus system and IEEE 118-bus system were used as case studies.

Simulation results from the PJM 5-bus system with a robust environmental-economic dispatch and absence of capture facilities gave a generating cost of $39,085 and carbon dioxide emission of 1166 tons, while the inclusion of contrived capture facilities led to a generating cost of $42, 123 and carbon dioxide emissions of 921 tons. The included capture facility led to an increase of 7.77% generating cost and a reduction of 26.6% carbon emission compared with the situation without capture facilities.

The carbon capture plants were also found to increase the system operating flexibility and enlarge the dispatchable region of wind power, as the energy consumption in capture facilities plays the role of spinning reserve capacity. Simulation results from the case studies of IEEE 118-bus system similarly verified the efficiency of the proposed methodology to perform the assigned task.

The proposed methodology in this study confirms that the combination of wind generation and carbon capture technology could provide an economic and environmental friendly operation for power systems, and the resulting dispatch problem can be solved in a theoretically sound manner.

About The Author

Wei Wei received the B.Sc. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 2008 and 2013, respectively.
He was a Postdoctoral Researcher with Tsinghua University from 2013 to 2015. He was a Visiting Scholar with the School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA, in 2014, and with the School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA, in 2015. He is currently an Assistant Professor with Tsinghua University.

His research interests include applied optimization and energy economics. He has authored more than 40 peer-reviewed journal papers, with special emphasis on the integration of large-scale renewable generation. Most of them are published in IEEE Transaction journals and Elsevier energy related periodicals. He is currently focusing on the operation and market issues of the networked energy systems, including the electric power grid, natural gas pipeline network, district heating network, and electrified transportation network.

About The Author

Feng Liu received the B.Sc. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 1999 and 2004, respectively.

He is currently an Associate Professor of Tsinghua University. His research interests include power system stability, control, and distributed optimization.

About The Author

Jianhui Wang received the Ph.D. degree in electrical engineering from Illinois Institute of Technology, Chicago, IL, USA, in 2007.

Dr. Jianhui Wang is the Section Manager for Advanced Power Grid Modeling in the Energy Systems division at Argonne National Laboratory. Dr. Wang is the Principal Investigator for a multitude of energy-related research projects focused on smart grid, microgrids, power system operation and control, renewable integration, grid resilience and cyber-security. He currently manages a group of 12 research staff and postdocs and 14 visiting students and scholars. In addition, he is a Fellow of the Computation Institute at The University of Chicago, an Adjunct Professor at the University of Notre Dame and an Affiliate Professor at Auburn University. He has also held visiting positions in Europe, Australia and Hong Kong including a VELUX Visiting Professorship at the Technical University of Denmark (DTU). He has been invited to give tutorials and keynote speeches at major conferences including IEEE SmartGridComm, IEEE SEGE, IEEE HPSC and IGEC-XI.

Dr. Wang is the secretary of the IEEE Power & Energy Society (PES) Power System Operations committee. Before being promoted and elected to this position, he was the chair of the IEEE PES Power System Operation Methods Subcommittee for six years. He is also the recipient of the IEEE Chicago Section 2012 Outstanding Young Engineer Award.

Dr. Wang has authored and/or co-authored more than 200 journal and conference publications, which have been cited for more than 5,000 times by his peers. He is an associate editor of Journal of Energy Engineering and an editorial board member of Applied Energy. He served as guest editor for a special issue of the IEEE Power and Energy Magazine on Electrification of Transportation, which won an APEX Grand Award. Dr. Wang also served as the editor of Artech House Publishers’ Power Engineering Book Series, and as the Technical Program Chair of the 2012 IEEE PES Innovative Smart Grid Technologies conference.

Dr. Wang is the Editor-in-Chief of the IEEE Transactions on Smart Grid and an IEEE PES Distinguished Lecturer. He is the recipient of the IEEE PES Power System Operation Committee Prize Paper Award in 2015.

About The Author

Shengwei Mei received the B.Sc. degree in mathematics from Xinjiang University, Urumqi, China, the M.Sc. degree in operations research from Tsinghua University, Beijing, China, and the Ph.D. degree in automatic control from Chinese Academy of Sciences, Beijing, China, in 1984, 1989, and 1996, respectively.

He is currently a Professor of Tsinghua University and a Fellow of the IEEE. His research interests include power system analysis and control, game theory and its application in power systems.

Journal Reference

W. Wei¹, F. Liu¹, J. Wang², L. Chen¹, S. Mei¹, T. Yuan³, Robust Environmental-Economic Dispatch Incorporating Wind Power Generation and Carbon Capture Plants, Applied Energy 183 (2016) 674–684.

Show Affiliations

1. Department of Electrical Engineering, Tsinghua University, 100084 Beijing, China
2. Argonne National Laboratory, Argonne, 60439 IL, USA.
3. Department of Electrical Engineering, Xinjiang University, 830046 Urumqi, China

 

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