Capacity Market for Distribution System Operator – with Reliability Transactions – Considering Critical Loads and Microgrids

Conventional distribution system (DS) asset planning methods consider energy only from transmission systems (TS) and not from distributed energy resources (DER), leading to expensive plans. Newer transactive energy DS (TEDS) asset planning models, built on capacity market mechanisms, consider energy from both TS and DERs, leading to lower-cost plans and maximizing social welfare. However, in both methods the cost of higher reliability requirements for some users are socialized across all users, leading to lower social welfare. In this paper, a novel transactive energy capacity market (TECM) model is proposed for DS asset planning. It builds on TEDS incremental capacity auction models by provisioning for critical loads to bid and receive superior reliability as a service. The TECM model considers these reliability transactions, in addition, to selling energy transactions from TS and DERs, buying energy transactions from loads, and asset upgrade transactions from the network operator. The TECM model allows for islanded microgrids and network reconfiguration to maximize social welfare. The TECM model is assessed on several case studies, demonstrating that it achieves higher social welfare and a lower plan cost

A New Methodology For The Optimal Charging Coordination Of Electric Vehicles Considering Vehicle-to-grid Technology

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)In this work, a new methodology based on a mixed integer linear programming formulation is proposed to solve the optimal charging coordination of electric vehicles (EVs) in unbalanced electrical distribution systems (EDS) considering vehicle-to-grid (V2G) technology. The steady-state operation of the EDS is represented using the real and imaginary parts of voltages and currents at nodes and circuits respectively. Distributed generation (DG) and the imbalance of the system circuits and loads are taken into account. The developed method defines an optimal charging schedule for the EVs. This charging schedule considers the EVs' arrival and departure times and their arrival state of charge, along with the energy contribution of EVs equipped with V2G technology. The presented formulation was tested in a 123-node distribution system. The charging schedule obtained was compared in terms of V2G and DG scenarios, demonstrating the efficiency of the proposed method.72596607CAPESCNPqFAPESPCPFLCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Optimal Volt-var Control Operation For Finergy Cost Reduction In Distribution Systems Considering A Voltage Dependent Load Model

In this paper, a new mixed integer linear programming formulation is proposed to optimally control the Volt-VAr control devices installed in a balanced electrical distribution system (EDS), taking into account the presence of dispatchable distributed generation (DG) units. The formulation considers a voltage dependent load model and aims to reduce the cost of the energy purchased to the substation and DG units on a daylong time period. The proposed method defines the settings for the voltage regulators, on-load tap changer, capacitors, and DG units. The presented formulation was tested in a 42-node EDS and the obtained results prove that the methodology enhances the EDS economic operation with a very low computational effort.IEEE PES Transmission & Distribution Conference and Exposition-Latin America (PES T&D-LA)SEP 20-24, 2016Morelia, MEXIC

Joint Optimal Operation of Photovoltaic Units and Electric Vehicles in Residential Networks with Storage Systems: A Dynamic Scheduling Method

The growing penetration of low–carbon technologies in residential networks such as photovoltaic generation (PV) units and electric vehicles (EVs) may cause technical issues on the grid. Thus, operation planning of electrical distribution networks (EDNs) should consider the inclusion of these technologies in order to avoid operational limit breaches. This paper proposes a dynamic scheduling method for an optimal operation of PV units and EVs in unbalanced residential EDNs, considering energy storage systems (ESSs). The proposed method optimizes the joint operation of PV units and EVs, using ESSs to increase the local consumption of the renewable energy. A rolling multi–period strategy based on a mixed integer linear programming model is used to dynamically optimize a centralized decision making, determining control actions for on-load tap changers (OLTCs), ESSs, PV units, and EVs connected to the network. At each time interval, data for PV generation and EV demand is updated using actual information and historical profiles, generating an updated forecast for a one-day-ahead operation in order to properly cope with weather uncertainties and EV owner’s behavior without the need of multiple scenarios. The effectiveness and robustness of this approach are verified in different cases via a 107–node test ED

A New Methodology for the Optimal Charging Coordination of Electric Vehicles Considering Vehicle-to-Grid Technology

Made available in DSpace on 2018-12-11T17:00:00Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-04-01Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)In this work, a new methodology based on a mixed integer linear programming formulation is proposed to solve the optimal charging coordination of electric vehicles (EVs) in unbalanced electrical distribution systems (EDS) considering vehicle-to-grid (V2G) technology. The steady-state operation of the EDS is represented using the real and imaginary parts of voltages and currents at nodes and circuits respectively. Distributed generation (DG) and the imbalance of the system circuits and loads are taken into account. The developed method defines an optimal charging schedule for the EVs. This charging schedule considers the EVs' arrival and departure times and their arrival state of charge, along with the energy contribution of EVs equipped with V2G technology. The presented formulation was tested in a 123-node distribution system. The charging schedule obtained was compared in terms of V2G and DG scenarios, demonstrating the efficiency of the proposed method.Departamento de Engenharia Elétrica Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista (UNESP)Department of Systems and Energy School of Electrical and Computer Engineering University of Campinas (UNICAMP)Departamento de Engenharia Elétrica Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista (UNESP

Hierarchical Optimization for User-Satisfaction-Driven Electric Vehicles Charging Coordination in Integrated MV/LV Networks

The growing uptake of electric vehicles (EVs) will likely require management schemes to enable their connection into distribution systems. While most of the existing approaches are developed from the operator's perspective considering EV aggregated demands at the medium-voltage (MV) level, individual users' comfort and the particularities associated with low-voltage (LV) networks need to be considered to holistically assess the EV effects in an integrated MV/LV network. This article proposes a two-level hierarchical optimization framework for the EV charging coordination (EVCC) that maximizes users' satisfaction, while avoiding operational grid issues in the whole distribution system. The framework is tailored for unbalanced distribution systems with high penetration of EVs and introduces a novel index to measure charging priority-based EV user satisfaction. To reduce the computational burden, the EVCC problem is disaggregated into an upper level for MV network operation, and a lower level for LV network and individual EV scheduling, using mixed-integer linear programming models. This framework is later embedded in a dynamic scheduling approach that copes with unexpected EV arrivals. Benefits (increased overall user satisfaction and reduced strain over distribution assets) are demonstrated via case studies in a 459-node three-phase network in which solutions were achieved under a 60-s threshold