2020
DOI: 10.1109/jsyst.2019.2921218
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Optimal CHP Planning in Integrated Energy Systems Considering Network Charges

Abstract: This paper proposes a novel optimal planning model for combined heat and power (CHP) in multiple energy systems of natural gas and electricity to benefit both networks by deferring investment for network owners and reducing use-of-system (UoS) charge for network users. The new planning model considers the technical constraints of both electricity and natural gas systems. A two-stage planning approach is proposed to determine the optimal site and size of CHPs. In the first stage, a long-run incremental cost (LR… Show more

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Cited by 19 publications
(4 citation statements)
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“…Where:  represents the simulated annealing penalty factor, t Represents the simulated annealing temperature, and the initial temperature needs to be given during the calculation 0 t ,  Represents the temperature cooling coefficient, usually between 0 and 1 23 .…”
Section: Model Solving Based On Improved Genetic Algorithmmentioning
confidence: 99%
“…Where:  represents the simulated annealing penalty factor, t Represents the simulated annealing temperature, and the initial temperature needs to be given during the calculation 0 t ,  Represents the temperature cooling coefficient, usually between 0 and 1 23 .…”
Section: Model Solving Based On Improved Genetic Algorithmmentioning
confidence: 99%
“…. m q is the mass flow rate injected into each node; B h is the loop incidence matrix; h f is the head losses; K h is the resistance coefficients of each pipe [31].…”
Section: Hydraulic Modelmentioning
confidence: 99%
“…Efforts have been devoted to decarbonising both energy supplies and energy consumption, e.g., promotion of renewable energy sources, and adoption of electric vehicles (EVs) to replace fossil-fuelled vehicles. Versatile energy converters, e.g., combined heat and power (CHP) generation, show great potentials in further improving energy efficiency by jointly meeting multiple energy demands [2]. This has stimulated a multi-vector energy system (MVES) modelling method that characterises the operations of multiple energy converters to better coordinate both supply and demand in multi-vector energy forms [3].…”
Section: Introductionmentioning
confidence: 99%