Now showing 1 - 10 of 25
  • Publication
    Robust optimization based EV charging
    (IEEE, 2014-12-19) ;
    With the introduction of new technologies like electric vehicles and smart grids the operation and planning of power systems are subject to major changes. These technologies can bring various flexibilities to different entities involved in decision making. This paper proposes a robust optimization based method to optimal charging/discharging of electric vehicles considering the electricity price uncertainties. The objective function is defined as the total operating costs of energy procurement in distribution networks which is tried to be minimized while considering the technical constraints of the problem.
      322Scopus© Citations 7
  • Publication
    Resilient Identification of Distribution Network Topology
    IEEE Network topology identification (TI) is an essential function for distributed energy resources management systems (DERMS) to organize and operate widespread distributed energy resources (DERs). In this paper, discriminant analysis (DA) is deployed to develop a network TI function that relies only on the measurements available to DERMS. The propounded method is able to identify the network switching configuration, as well as the status of protective devices. Following, to improve the TI resiliency against the interruption of communication channels, a quadratic programming optimization approach is proposed to recover the missing signals. By deploying the propounded data recovery approach and Bayes' theorem together, a benchmark is developed afterward to identify anomalous measurements. This benchmark can make the TI function resilient against cyber-attacks. Having a low computational burden, this approach is fast-track and can be applied in real-time applications. Sensitivity analysis is performed to assess the contribution of different measurements and the impact of the system load type and loading level on the performance of the proposed approach.
      257Scopus© Citations 13
  • Publication
    Resilient Decentralized Control of Inverter-interfaced Distributed Energy Sources in Low-voltage Distribution Grids
    (Institution of Engineering and Technology, 2019-10-29) ; ;
    Abstract: This paper shows that a relation can be found between the voltage at the terminals of an inverter-interfaced Renewable Energy Source (RES) and its optimal reactive power support. This relationship, known as Volt-Var Curve (VVC), enables the decentral operation of RES for Active Voltage Management (AVM). In this paper, the decentralized AVM technique is modified to consider the effects of the realistic operational constraints of RES. The AVM technique capitalizes on the reactive power support capabilities of inverters to achieve the desired objective in unbalanced active Low-Voltage Distribution Systems (LVDSs). However, as the results show, this AVM technique fails to satisfy the operator’s objective when the network structure dynamically changes. By updating the VVCs according to the system configuration and components’ availability, the objective functions will be significantly improved, and the AVM method remains resilient against the network changes. To keep the decentralized structure, the impedance identification capability of inverters is used to find the system configuration locally. Adaptive VVCs enable the decentralized control of inverters in an online setting. A real-life suburban residential LV-DS in Dublin, Ireland is used to showcasing the proposed method, and the effectiveness of the proposed resilient active voltage management technique is demonstrated.
    Scopus© Citations 3  259
  • Publication
    Distribution networks' energy losses versus hosting capacity of wind power in the presence of demand flexibility
    With the increasing share of renewable energy sources (RES) in demand supply, the distribution network operators (DNOs) are facing with new challenges. In one hand, it is desirable to increase the ability of the network in absorbing more renewable power generation units (or increasing the hosting capacity (HC)). On the other hand,  power injection to the distribution network by renewable resources may increase the active power losses (if not properly allocated) which reduces the efficiency of the network. Thus, the DNO should make a balance between these two incommensurate objective functions. The Demand Response (DR) in context of smart grids can be used by DNO to facilitate this action. This paper provides an approach in which a multi-objective and multi-period NLP optimization model is formulated where the DR is utilized as an effective tool to increase HC and decrease the energy losses simultaneously. In order to quantify the benefits of the proposed method, it is applied on a 69-bus distribution network. The numerical results substantiate that the proposed approach gives optimal locations and capacity of RES, as well as minimum energy losses by load shifting capability provided via DR programs.
    Scopus© Citations 58  504
  • Publication
    Resiliency oriented integration of Distributed Series Reactors in transmission networks
    Secure and reliable operation of power system in normal and contingency conditions is of great importance for system operator. Natural disasters can seriously threaten power systems normal operation with catastrophic consequences. While hardening approaches may be considered for resiliency improvement, an application of a new and cost effective technology is proposed in this paper. This work proposes a planning procedure for integrating Distributed Series Reactors (DSR) into transmission grids for improving the resiliency against these disasters. DSRs are able to control power flows through meshed transmission grids and thus improve the power transfer capability. This can improve the penetration level of renewable generation as well which is addressed in this paper. The problem of integrating DSRs into transmission grids is formulated as a mixed integer linear programming problem. Different load and wind profiles and a predefined number of disaster scenarios are considered in evaluating the impacts of DSR deployment on system’s operational costs, wind curtailment and load shedding during disasters and normal condition. The uncertainty of wind generation can affect economic viability of DSRs deployment thus; an information gap decision theory based method is proposed for uncertainty handling. The proposed methodology is implemented on the IEEE-RTS 24 bus test system and results show the functionality of DSRs in converting the conventional transmission grid into a flexible and dispatchable asset.
    Scopus© Citations 30  454
  • Publication
    Distribution Network Operation Under Uncertainty Using Information Gap Decision Theory
    The presence of uncertain parameters in electrical power systems presents an ongoing problem for system operators and other stakeholders when it comes to making decisions.Determining the most appropriate dispatch schedule or system configuration relies heavily on forecasts for a number of parameters such as demand, generator availability and more recently weather. These uncertain parameters present an even more compelling problem at the distribution level, as these networks are inherently unbalanced, and need to be represented as such for certain tasks. The work in this paper presents an information gap decision theory based three-phase optimal power flow. Assuming that the demand is uncertain, the aim is to provide optimal and robust tap setting and switch decisions over a 24-hour period,while ensuring that the network is operated safely, and that losses are kept within an acceptable range. The formulation is tested on a section of realistic low voltage distribution network with switches and tap changers present.
    Scopus© Citations 34  1080
  • Publication
    A data‐driven measurement placement to evaluate the well‐being of distribution systems operation
    (Institution of Engineering and Technology, 2021-01-05) ; ;
    The widespread integration of intelligent electronic devices has facilitated the employment of data mining methods in evaluating the operating condition of distribution systems. This possibility comes to prominence in active networks, where distributed energy resources can cause unforeseen dynamics that requires an effective monitoring infrastructure and a fast‐track procedure to convey the system operating condition in a comprehensible manner to the operator. To this end, a data‐driven approach is proposed to assess the status of system operating constraints by presenting each constraint as a classification problem. Afterwards, by exploiting the propounded presentation of the system operating condition, the measurement placement problem in distribution systems is addressed as selecting a set of features that have the most contribution to evaluating the system operating status . To do so, first, the effectiveness of the measurement units is identified through their contribution to the classification process, and then a procedure is proposed to pinpoint the measurement units with redundant information. Monte–Carlo simulations are performed to provide a comprehensive training set. Receiver operating characteristic analysis and time‐series power flows demonstrate the effectiveness of the proposed approaches.
    Scopus© Citations 3  168
  • Publication
    Restoration in a Self-healing Distribution Network with DER and Flexible Loads
    This paper develops an algorithm for energy management of a distribution network considering a restorative plan for most possible devastating contingencies in the network. The distribution network is selfhealing and consists of smart meters and remotely controlled automated switches. Distributed energy resources and flexible loads provide the redundant capacity for restoration. Under normal operating conditions, the objective of the energy management system is to minimize the generation cost, while under emergency conditions, the objective is to minimize the amount of shed load, giving priority to critical loads. The energy management problem forms a non-linear programming problem. Simulation results verify the effectiveness of the proposed algorithm in energy management and restoration of a distribution network.
      413Scopus© Citations 7
  • Publication
    Information Gap Decision Theory based OPF with HVDC Connected Wind Farms
    (Institute of Electrical and Electronics Engineers, 2014-12) ; ;
    A method for solving the optimal power flow (OPF) problem including HVDC connected offshore wind farms is presented in this paper. Different factors have been considered in the proposed method, namely, voltage source converter (VSC-HVDC) and line-commutated converter high-voltage DC (LCC-HVDC) link constraints, doubly fed induction generators' (DFIGs) capability curve as well as the uncertainties of wind power generation. Information gap decision theory (IGDT) is utilized for handling the uncertainties associated with the volatility of wind power generation. It is computationally efficient and does not require the probability density function of wind speed. The proposed decision-making framework finds the optimal decision variables in a way that they remain robust against the considered uncertainties. To illustrate the effectiveness of the proposed approach, it is applied on the IEEE 118-bus system. The obtained results validate the applicability of the proposed IGDT-based OPF model for optimal operation of AC/DC power systems with high penetration of offshore wind farms.
    Scopus© Citations 106  791
  • Publication
    Optimal DR and ESS Scheduling for Distribution Losses Payments Minimization Under Electricity Price Uncertainty
    The distribution network operator is usually responsible for increasing the efficiency and reliability of network operation. The target of active loss minimization is in line with efficiency improvement. However, this approach may not be the best way to decrease the losses payments in an unbundled market environment. This paper investigates the differences between loss minimization and loss payment minimization strategies. It proposes an effective approach for decreasing the losses payment considering the uncertainties of electricity prices in a day ahead energy market using energy storage systems and demand response. In order to quantify the benefits of the proposed method, the evaluation of the proposed technique is carried out by applying it on a 33-bus distribution network.
    Scopus© Citations 131  973