4 research outputs found
Increasing distributed generation hosting capacity in distributionsystems via optimal coordination of electric vehicle aggregators
This work presents a novel strategy, designed from the distribution system operator view-point, aimed at estimating the hosting capacity in electric distribution systems when con-trollable plug-in electric vehicles are in place. The strategy seeks to determine the maxi-mum wind-based distributed generation penetration by coordinating, on a forecast basis,the dispatch of electric vehicle aggregators, the operation of voltage regulation devices,and the active and reactive distributed generation power injections. Different from previ-ous works, the proposed approach leverages controllable features of electric vehicles takinginto account technical electric vehicle characteristics, driving behaviour of electric vehicleowners, and electric vehicle energy requirements to accomplish their primary purpose. Thepresented strategy is formulated as a two-stage stochastic mixed-integer linear program-ming problem. The first stage maximises the distributed generation installed capacity, whilethe second stage minimises the energy losses during the planning horizon. Probability den-sity functions are used to describe the uncertainties associated with renewable distributedgeneration, conventional demand, and electric vehicle driving patterns. Obtained resultsshow that controlling the power dispatched to electric vehicle aggregators can increase thedistributed generation hosting capacity by up to 15% (given a 40% electric vehicle penetra-tion), when compared to an uncontrolled electric vehicle approac
Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system
The optimal management of distributed energy resources (DERs) and renewable-based generation in multi-energy systems (MESs) is crucial as it is expected that these entities will be the backbone of future energy systems. To optimally manage these numerous and diverse entities, an aggregator is required. This paper proposes the self-scheduling of a DER aggregator through a hybrid Info-gap Decision Theory (IGDT)-stochastic approach in an MES. In this approach, there are several renewable energy resources such as wind and photovoltaic (PV) units as well as multiple DERs, including combined heat and power (CHP) units, and auxiliary boilers (ABs). The approach also considers an EV parking lot and thermal energy storage systems (TESs). Moreover, two demand response (DR) programs from both price-based and incentive-based categories are employed in the microgrid to provide flexibility for the participants. The uncertainty in the generation is addressed through stochastic programming. At the same time, the uncertainty posed by the energy market prices is managed through the application of the IGDT method. A major goal of this model is to choose the risk measure based on the nature and characteristics of the uncertain parameters in the MES. Additionally, the behavior of the risk-averse and risk-seeking decision-makers is also studied. In the first stage, the sole-stochastic results are presented and then, the hybrid stochastic-IGDT results for both risk-averse and risk-seeker decision-makers are discussed. The proposed problem is simulated on the modified IEEE 15-bus system to demonstrate the effectiveness and usefulness of the technique.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed
Placing the Origin of Two Species-Rich Genera in the Late Cretaceous with Later Species Divergence in the Tertiary: A Phylogenetic, Biogeographic and Molecular Dating Analysis of \u3cem\u3ePiper\u3c/em\u3e and \u3cem\u3ePeperomia\u3c/em\u3e (Piperaceae)
Nearly all of the species diversity in Piperaceae is encompassed within Piper and Peperomia. Both genera are pan-tropical with areas of diversification in the Neotropics and Southeast Asia. Piperaceae are less diverse in Africa with only two native species of Piper. This study examines the distribution of both Piper and Peperomia with representative samples from the Neotropics, Asia, Pacific Islands, and Africa. Molecular dating is used to place an age for the crown clades of Piper and Peperomia as well as ages for diversification within the clades. Both genera have origins in the late Cretaceous, but species level diversification occurred much later in the Tertiary. Biogeography of both genera are correlated with paleoclimate evidence to better explain the distribution and diversification of these large genera