Emission Reduction and Economical Optimization of an Urban Microgrid Operation Including Dispatched PV-Based Active Generators

Kanchev, Hristiyan; Colas, Frédéric; Lazarov, Vladimir; Bart, François

doi:10.1109/tste.2014.2331712

Cited by 166 publications

(104 citation statements)

References 24 publications

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“…Depending on the types of energy systems included in the problem, these formulations can be classified into two groups. Some of these algorithms only focus on electrical energy flow and neglect the thermal energy flow, e.g., [10][11][12][13][14][15][16][17][18][19][20][21][22]. However, in microgrids, optimal dispatch of thermal resources is as important as electrical resources, and simultaneous optimization of thermal and electrical resources is of great importance, especially when the two are linked through CHP-enabled technologies [23].…”

Section: The Distributed Energy Resource Customer Adoption Modelmentioning

confidence: 99%

“…The maximum daily energy cost constraint can be shown as (22), in which the energy rates at each time are the RTP rates, as shown in (23). In (22), RTPMaxCost is the maximum allowed daily energy cost for the customer, and is used to keep the problem feasible, if the goal cannot be achieved after shedding all possible loads. For this purpose, a new term, × , is added to the optimization objective function, as shown in (25), in which is an arbitrary large number.…”

Section: Model For Real-time Pricingmentioning

confidence: 99%

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Distributed energy systems integration and demand optimization for autonomous operations and electric grid transactions

et al. 2016

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Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. This paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California-Fort Hunter Liggett (FHL). The results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.

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Section: The Distributed Energy Resource Customer Adoption Modelmentioning

confidence: 99%

Section: Model For Real-time Pricingmentioning

confidence: 99%

Distributed energy systems integration and demand optimization for autonomous operations and electric grid transactions

et al. 2016

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“…Moreover, DC is chosen over AC because it facilitates integrating most modern electronic loads, energy storage devices, and DG technologies-all of them inherently DC.  Economical operation [13][14][15]: Economical operation in DC microgrids can be achieved without complex and computation-intensive optimization algorithms and as pointed out in the existing literature, the total cost of ownership, infrastructure, equipment, maintenance and operation are lower in DC microgrids.  Efficiency [16][17][18]: The system efficiency becomes higher due to the reduction of conversion losses of inverters between DC output sources and loads.…”

Section: State-of-the-art Of DC Microgridsmentioning

confidence: 99%

Enhanced Load Power Sharing Accuracy in Droop-Controlled DC Microgrids with Both Mesh and Radial Configurations

Liu

Wang

et al. 2015

Energies

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The rational power sharing among different interface converters should be determined by the converter capacity. In order to guarantee that each converter operates at the ideal condition, considering the radial and mesh configuration, a modified strategy for load power sharing accuracy enhancement in droop-controlled DC microgrid is proposed in this paper. Two compensating terms which include averaging output power control and averaging DC voltage control of neighboring converters are employed. Since only the information of the neighboring converter is used, the complexity of the communication network can be reduced. The rational distribution of load power for different line resistance conditions is realized by using modified droop control that can be regarded as a distributed approach. Low bandwidth communication is used for exchanging sampled information between different converters. The feasibility and effectiveness of the proposed method for different network configurations and line resistances under different communication delay is analyzed in detail. Simulation results derived from a DC microgrid with three converters is implemented in MATLAB/Simulink to verify the proposed approach. Experimental results from a 3 × 10 kW prototype also show the performance of the proposed modified droop control scheme.

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“…Another important issue may be the necessity of galvanic isolation. When higher output power is needed, modular system topology is often used with several converters operating in parallel to a common load [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Resonant Converters for Energy Storage Systems

2017

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Abstract.The following paperwork presents a comparative analysis of multiphase resonant converters for applications in energy storage systems. Models of the examined converters are developed in the software environments of MATLAB and LTspice. Results from the simulation examination of the converters during charging of supercapacitors and rechargeable batteries are presented. These results are compared to results obtained from experimental examination of the converters via a laboratory stand. For the purposes of the experimental examination, a control system is developed on the base of a virtual instrument in LabVIEW. The advantages and disadvantages of the different converters are discussed.

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Emission Reduction and Economical Optimization of an Urban Microgrid Operation Including Dispatched PV-Based Active Generators

Cited by 166 publications

References 24 publications

Distributed energy systems integration and demand optimization for autonomous operations and electric grid transactions

Distributed energy systems integration and demand optimization for autonomous operations and electric grid transactions

Enhanced Load Power Sharing Accuracy in Droop-Controlled DC Microgrids with Both Mesh and Radial Configurations

Comparative Analysis of Resonant Converters for Energy Storage Systems

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