Omid Alizadeh-Mousavi

The intermittencies of renewable generations give rise to situations, which require both slow‐ and fast‐ramping flexibility capability from a variety of resources connected at the medium voltage (MV) andlow voltage (LV) distribution grids. Moreover, this may increase the grid reinforcement costs. To defer this reinforcement, the grid needs to be operated optimally. This paper proposes—(a) such an optimal operational methodology forthe MV and LV grids; and (b) an aggregated flexibility estimation methodology separately for fast and slow services at the primary substation (transmission interface). The methodologies based on model‐based MV grids and sensitivity coefficients‐based LV grids are suitable for LV grids where an up‐to‐date, accurate model and topology are not always available. Besides, the costs and resources associated to create full LV grid model and visibility should be prevented. The approaches, here, use the synchronised and accurate measurements from grid monitoring devices located at the LV distribution grids. They have been validated on a real MV and LV networks of a Swiss distribution grid operator equipped with such devices. The results, in terms of reducing technical losses, reducing grid violation costs,and estimating flexibility capability show the efficacy of the proposed methodologies and therefore, can be easily deployed.

The dynamic nature of power systems operation, lack of sufficient monitoring initiatives, and the continuous nature of the power quality phenomena are the primary reasons behind a distribution system operator's inability to localize and understand the root cause behind unbalance. Additionally, there is a deficiency of algorithms that can leverage the grid monitoring data, even if limited, to present a sufficiently useful overview of unbalance propagation which can lead to appropriate corrective measures. This article presents: a new unbalance index derived from feeder active power measurements, an algorithm for localization of unbalanced contributions, and an algorithm for root cause analysis that can distinguish whether the unbalance problem is loading, asymmetry, and/ or fault-oriented. The end goals of this work are twofold: to present a holistic view of the grid unbalanced situation using EN50160 type monitoring, and to assist the distribution system operators in unbalance reduction. The usability of the proposed algorithms and indices is shown using a hybrid European MV-LV model simulated in OpenDSS and on two actual LV distribution systems with real-time power quality monitoring.

This paper presents a rolling horizon optimal energy management mechanism using real-time grid monitoring data. The proposed mechanism includes novel approaches in terms of real-time data processing, net-load forecasting, and optimal scheduling of battery energy storage systems. The proposed real-time data processing and net-load forecasting techniques use fast training and computationally efficient methods based on grid monitoring data. The data processing and parameter forecasting methods are based on auto-regressive with exogenous variables (ARX). Two sets of features including similar values in previous hours, days, and weeks as well as calendar effects are used for training the forecast model. Furthermore, the impact of additional non-synchronized weather features adopted from meteorology databases on the forecasts’ accuracy is discussed. Finally, a real-time optimal scheduling is proposed to optimize battery energy storage systems (BESS), maximizing the self-consumption at grid and community levels. The application of real-time grid measurement in the proposed algorithm allows handling the impacts of loads and generators behind the meter without having their detailed information. The developed method is being effectively used in a real low voltage distribution grid in Switzerland.

Real-time monitoring of distribution systems has become necessary, due to the deregulation of electricity markets and the wide deployment of distributed energy resources. To monitor voltage and current at sub-cycle detail, requires, typically, major investment undertaking and disruptions to the operation of the grid. In this work, measurements of the low voltage (LV) side of distribution transformers (T/F) are used to calculate in real time the waveforms of their medium voltage (MV) sides, based on a mathematical model of said T/F. This model is, essentially, the digital twin of the MV side of the T/F. The method calculates T/F MV waveforms of voltage and current, and active and reactive power as accurately as an instrument T/F, captures all harmonics content, is unaffected by asymmetrical loading and identifies most system faults on the MV side of the T/F. The digital twin method enables monitoring of distribution T/F that avoids MV instrumentation, does not suffer in accuracy and may be readily deployable. Field data from an actual MV-LV T/F, agree with simulation results showcasing the efficacy of the digital twin method.

This paper combines two planning problems into a single planning problem and numerically shows the benefits of their combination. Specifically, we combine the optimal transmission expansion planning problem and the optimal placement of thyristor controlled series compensators (TCSCs) in a transmission network. The proposed single period math program for the combined problem minimizes the investment costs of the new lines and TCSCs and the expected costs of generation and load shed while multiple operation scenarios are considered. The model relies on the dc approximation of the power flow network and ties the maximum flow limit of each line to its length. The operation scenarios are developed by considering the load and wind power generation of a specific period using a proposed method for scenario reduction. The general linearization technique and the disjunctive model are used to linearize the polynomial constraints in the problem. The numerical results for solving the proposed optimization model for the Graver 6-bus and the IEEE 118-bus systems show the cost benefits and wind penetration of using the proposed combined planning model.

The Pumped Hydro Storages (PHSs) equipped with variables speed drives have several advantages, namely: i) power regulation in pumping mode, ii) extended operating range, iii) higher efficiency in turbine mode. Such flexible operation of the PHS units ensures capability of the PHS to provide the frequency control reserves even during the pumping mode. It may lead to increased revenues in the electricity market conditions. It is important to quantify the benefits of PHS, especially variable-speed ones. This paper proposes a Stochastic Security Constrained Unit Commitment (SSCUC) model which takes into account different models of pumped hydro units. Different energy and reserve provision models are considered for fixed-speed and variable-speed units in the generating and pumping modes. The presented day-ahead SSCUC problem considers the optimization of energy and reserves costs. The problem is solved using Benders decomposition approach, for which the master problem solves the unit commitment and the sub-problems ensure the feasibility of the solution for the base operating point and for a set of dedicated scenarios. The set of scenarios includes the base operating point, contingencies (i.e. N-1 criterion), and stochasticity of demand and renewable injections. The proposed formulation is successfully tested on IEEE RTS 24-bus system.

This paper proposes a scalable and computationally efficient approach aimed at integrating the Dynamic Line Rating (DLR) of Overhead Transmission Lines (OTLs) in AC-Optimal Power Flow (AC-OPF) problem. The proposed multi-period formulation takes into account realistic models of the different terms of the Heat-Balance Equation (HBE) applied to OTL conductors. These terms are appropriately incorporated in order to preserve the convexity of the OPF that, in this paper, refers to the case of real-time dispatching of a given number of generation units. In this respect, a linearized formulation of AC-OPF is used in the problem definition. The proposed methodology is tested using a small standard case study as well as the IEEE 24 and 118 buses test networks. The results show that the proposed methodology increases the security of the system in conjunction to the capability to decrease the operation cost.

The integration of the dynamic line rating (DLR) of overhead transmission lines (OTLs) in power systems security constrained unit commitment (SCUC) potentially enhances the overall system security as well as its technical/economic performances. This paper proposes a scalable and computationally efficient approach aimed at integrating the DLR in SCUC problem. The paper analyzes the case of the SCUC with AC load flow constraints. The AC-optimal power flow (AC-OPF) is linearized and incorporated into the problem. The proposed multi-period formulation takes into account a realistic model to represent the different terms appearing in the Heat-Balance Equation (HBE) of the OTL conductors. In order to include the HBE in the OPF, a relaxation is proposed for the heat gain associated to resistive losses while the inclusion of linear approximations are investigated for both convection and radiation heat losses. A decomposition process relying on the Benders decomposition is used in order to breakdown the problem and incorporate a set of contingencies representing both generators and line outages. The effects of different linearization, as well as time step discretization of HBE, are investigated. The scalability of the proposed method is verified using IEEE 118-bus test system.