Dynamic analysis of hybrid energy systems under flexible operation and variable renewable generation – Part I: Dynamic performance analysis

García, Humberto E.; Mohanty, Amit; Lin, Wen-Chiao; Cherry, Robert

doi:10.1016/j.energy.2013.01.022

Cited by 62 publications

(32 citation statements)

References 40 publications

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“…The drawback of such a configuration is that in case the energy supply exceeds the demand, excess energy is either wasted or must be transferred to large storage devices, which are expensive. Therefore, the MIMO system can be expected to offer significant advantages in flexbility, utilization and efficiency over the MISO system, as reported in, for example, [3,4]. Note that the HES considered here contains two types of energy flows: thermal (in the form of heated helium) and electrical.…”

Section: Hes Modelmentioning

confidence: 99%

An Optimization Framework for Dynamic Hybrid Energy Systems

Du¹,

García²,

Paredis³

2014

Linköping Electronic Conference Proceedings

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A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid energy system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes intrinsic properties of the base generation, power cycle, and electrical storage components to minimize variability in the HES. The second problem takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. Variability in electrical power applied to high temperature steam electrolysis is shown to be reduced by 18% in the unconstrained case and 11% in the constrained case. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.

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Section: Hes Modelmentioning

confidence: 99%

An Optimization Framework for Dynamic Hybrid Energy Systems

Du¹,

García²,

Paredis³

2014

Linköping Electronic Conference Proceedings

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“…Although several parameters implicitly comprise geospatial data attributes, such as the -location‖ of wind farms and -neighboring‖ locations, geographic methods for investigating geographic patterns, such as the spatio-temporal development of energy fluctuations, are not considered. Furthermore, the problem of such energy fluctuations caused by varying renewable energy generation and flexible network operation within hybrid energy systems is comprehensively discussed in terms of economic aspects, specifically the dynamic cost of integrating renewable energy into the power grid [36,37]. -From accommodating ever increasing levels of renewable penetration‖, the authors conclude that the -direct integration of variable renewable generation poses fundamental technical challenges, because of its high variability, unpredictability and non-dispatchability‖, but the geospatial dimension of such energy fluctuations is neglected.…”

Section: Non-gis-based Approaches (Non-geospatial Methods)mentioning

confidence: 99%

GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

Resch

Sagl

Törnros

et al. 2014

IJGI

124

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Abstract:In the face of the broad political call for an -energy turnaround‖, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS) is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future OPEN ACCESS ISPRS Int. J. Geo-Inf. 2014, 3 663 research avenues comprise the availability base data and their -geospatial awareness‖, the development of a generic and unified data model, the usage of volunteered geographic information (VGI) and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design.Keywords: integration of GIS and energy system models; GIS and renewable energy; GIS-based energy infrastructure planning; future research challenges; fluctuating renewables; structural planning of local energy systems; operation optimization

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“…total pressure p T, 6 and total temperature T T,6 ) are assumed to be known by virtue of the thermodynamic state calculation, to the throat, where sonic conditions are attained, i.e., the flow speed equals the speed of sound c. The corresponding equations are:…”

Section: Supersonic Turbinementioning

confidence: 99%

“…In a recent work, Garcia et al [6] investigated options to increase the robustness of energy networks, by simulating energy flow scenarios in which multiple forms of energy commodities, such as electricity and chemical products, may be exchanged. They studied the interactions between the grid and such advanced hybrid energy systems, by using dynamic models of various units and simulating their operation.…”

Section: Introductionmentioning

confidence: 99%

Design methodology for flexible energy conversion systems accounting for dynamic performance

Pierobon

Casati

Casella

et al. 2014

Energy

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This article presents a methodology to help in the definition of the optimal design of power generation systems. The innovative element is the integration of requirements on dynamic performance into the system design procedure. Operational flexibility is an increasingly important specification of power systems for base-and part-load operation. Thus, it is crucial to discard, in an early phase of the design process, plant configurations which feature unacceptable dynamic performance. The test case is the preliminary design of an off-grid power plant serving an off-shore platform where one of the three gas turbines is combined with an organic Rankine cycle turbogenerator to increase the overall energy efficiency. At the core of the procedure is a stationary model, capable of performing the on-design thermodynamic cycle calculation, and the design of the components of the system. The results of these simulations are used within the framework of a multi-objective optimization procedure to identify a number of equally optimal system configurations. A dynamic model of each of these systems is automatically parameterized, by inheriting its parameters values from the design model. Dynamic simulations allow then to discriminate among the initial set of solutions, thus providing the designs that also comply with dynamic requirements.

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Dynamic analysis of hybrid energy systems under flexible operation and variable renewable generation – Part I: Dynamic performance analysis

Cited by 62 publications

References 40 publications

An Optimization Framework for Dynamic Hybrid Energy Systems

An Optimization Framework for Dynamic Hybrid Energy Systems

GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

Design methodology for flexible energy conversion systems accounting for dynamic performance

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