13 results found
Nduka OS, Kunjumuhammed L, Pal B, et al., 2019, Field trial of coordinated control of PV and energy storage units and analysis of power quality measurements, IEEE Access, Vol: 8, Pages: 1962-1974, ISSN: 2169-3536
Trends support low voltage distribution networks will soon experience significant uptake of customer-owned low-carbon technology (LCT) devices especially rooftop photovoltaics (PVs) and small-scale energy storage (SSES) systems. This paradigm shift will introduce some significant challenges in modern distribution network planning and operations owing to the temporal nature of modern demand.Therefore, it became relevant to investigate the UK low voltage (LV) network operations considering high uptake of PVs and SSESs through both field measurements and desktop studies. The aim was to validatethrough field trials, the flexibility benefits of peak demand reduction and reverse power flow mitigation through smart control of customer-owned SSESs. It was shown that peak demand of up to 60% could beachieved in UK distribution network through the smart control of these devices. In tandem with the demand reduction, the study revealed that type-tested SSES power interface units do not pose significant powerquality risks even for 100% customer penetration.
Majumdar A, Pal BC, 2018, Bad data detection in the context of leverage point attacks in modern power networks, IEEE Transactions on Smart Grid, Vol: 9, Pages: 2042-2054, ISSN: 1949-3061
This paper demonstrates a concept to detect bad data in state estimation when the leverage measurements are tampered with gross error. The concept is based on separating leverage measurements from non-leverage measurements by a technique called diagnostic robust generalized potential (DRGP), which also takes care of the masking or swamping effect, if any. The methodology then detects the erroneous measurements from the generalized studentized residuals (GSR). The effectiveness of the method is validated with a small illustrative example, standard IEEE 14-bus and 123-bus unbalanced network models and compared with the existing methods. The method is demonstrated to be potentially very useful to detect attacks in smart power grid targeting leverage points in the system.
Majumdar A, Agalgoankar YP, Pal BC, et al., 2017, Centralized volt-var optimization strategy considering malicious attack on distributed energy resources control, IEEE Transactions on Sustainable Energy, Vol: 9, Pages: 148-156, ISSN: 1949-3037
The adoption of information and communication technology (ICT) based centralized volt-var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and thus can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt var optimization-distribution system state estimation (VVO-DSSE) malicious attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus UK generic distribution system (UKGDS) and validated against Monte Carlo simulations.
Nanchian S, Majumdar A, Pal BC, 2017, Ordinal optimization technique for three phase distribution network state estimation including discrete variables, IEEE Transactions on Sustainable Energy, Vol: 8, Pages: 1528-1535, ISSN: 1949-3037
This paper has discussed transformer tap position estimation with continuous and discrete variables in the context of three phase distribution state estimation (SE). Ordinal optimization (OO) technique has been applied to estimate the transformer tap position for the first time in unbalanced three phase distribution network model. The results on 129 bus system model have demonstrated that OO method can generate a reliable estimate for transformer exact tap position with discrete variables in distribution system state estimation (DSSE) and also in short period of time. In this paper the node voltages and power losses are calculated for 129 bus network. It is also demonstrated that OO is much faster than other accurate methods such HPSO. The losses obtained with OO are much accurate. In view of this OO performs better than WLS as it provides higher accuracy of the loss calculation. In a distribution network where about 5-6% of electricity generated is lost, accurate estimation of this loss has significant technical and commercial value. The authors believe the technique proposed will help realize those benefits.
Mokryani G, Majumdar ANKUR, Pal BC, 2016, A Probabilistic Method for the Operation of Three-Phase Unbalanced Active Distribution Networks, IET Renewable Power Generation, Vol: 10, Pages: 944-954, ISSN: 1752-1416
This paper proposes a probabilistic multi-objective optimization method for the operation of three-phase distribution networks incorporating active network management (ANM) schemes including coordinated voltage control and adaptive power factor control. The proposed probabilistic method incorporates detailed modelling of three-phase distribution network components and considers different operational objectives. The method simultaneously minimizes the total energy losses of the lines from the point of view of distribution network operators (DNOs) and maximizes the energy generated by photovoltaic (PV) cells considering ANM schemes and network constraints. Uncertainties related to intermittent generation of PVs and load demands are modelled by probability density functions (PDFs). Monte Carlo simulation method is employed to use the generated PDFs. The problem is solved using ɛ-constraint approach and fuzzy satisfying method is used to select the best solution from the Pareto optimal set. The effectiveness of the proposed probabilistic method is demonstrated with IEEE 13- and 34- bus test feeders.
Majumdar A, 2016, Security in power system state estimation
Majumdar A, Pal BC, 2016, A three-phase state estimation in unbalanced distribution networks with switch modelling, 1st IEEE International Conference on Control, Measurement and Instrumentation (CMI), Publisher: IEEE, Pages: 474-478
State estimation has become an important task in modern energy/distribution management systems. However, the state estimation is not very popular in modern unbalanced three-phase distribution systems. This paper proposes a method for three-phase state estimation with detailed three-phase modelling of system components including switches and star and delta connected loads. This method is then tested on a standard IEEE 13-bus system and the results are compared with load flow results.
Nanchian S, Majumdar A, Pal BC, 2015, Three-Phase State Estimation Using Hybrid Particle Swarm Optimization, IEEE Transactions on Smart Grid, Vol: PP, Pages: 1-11, ISSN: 1949-3061
This paper proposes a method for three-phase stateestimation (SE) in power distribution network including on-loadtap changers (OLTC) for voltage control. The OLTC tap positionsare essentially discrete variables from the SE point ofview. Estimation of these variables in SE presents a formidablechallenge. The proposed methodology combines discrete andcontinuous state variables (voltage magnitudes, angles, and tappositions). A hybrid particle swarm optimization (HPSO) isapplied to obtain the solution. The method is tested on standardIEEE 13- and 123-bus unbalanced test system models. Theproposed algorithm accurately estimates the network bus voltagemagnitudes and angles, and discrete tap values. The HPSO-basedtap estimation provides a more accurate estimation of losses inthe network, which helps in fair allocation of cost of losses inarriving at overall cost of electricity
Nanchian S, Majumdar A, Pal BC, et al., 2014, Transformer Tap Estimation Using Hybrid Particle Swarm Optimization, IEEE PES General Meeting, Publisher: IEEE, ISSN: 1944-9925
Majumdar A, Dimitrakopoulos S, Alizadeh-Mousavi O, Grid Monitoring for Efficient Flexibility Provision in Distribution Grids
The increased flexibility requirement needs a flexibility market at thedistribution grid level operated by the distribution system operators (DSOs) toresolve challenges to ensure secure operation and, to integrate new renewableproductions or loads in the grid. Therefore, the network visibility andmonitoring are paramount to distribution network operation. This paper presentsa methodology demonstrating the value distribution grid monitoring can bringfor the realisation of a local flexibility market. This paper furtherillustrates the reduction of costs of operation of a DSO with the help of gridmonitoring and local flexibility market while maintaining a secure and reliableoperation. The methodology has been applied on a real 35 node MV network of aSwiss DSO with several GridEye measurement devices. The performance in terms oflosses and voltage and flow violation costs is compared with sub-optimaloperation without monitoring.
Majumdar A, Alizadeh-Mousavi O, Grid-Aware Provision and Activation of Fast and Slow Flexibilities from Distributed Resources in Low and Medium Voltage Grids
As more and more renewable intermittent generations are being connected tothe distribution grid, the grid operators require more flexibility to maintainthe balance between supply and demand. The intermittencies give rise tosituations which require not only slow-ramping flexibility capability but also,fast-ramping flexibility capability from a variety of resources connected atthe MV and LV distribution grids. Moreover, the intermittencies may increasethe costs of grid reinforcement. Therefore, to defer the reinforcement of thegrid assets, the grid needs to be operated optimally. This paper proposes - a)such an optimal operational methodology for the MV and LV grids; and b) anaggregated flexibility estimation methodology estimated separately for fast andslow services at the primary substation (TSO interface). The methodologiesbased on model-based MV grids and a sensitivity coefficients-based model-lessLV grids are suitable for LV grids where an up-to-date and accurate model andtopology are not always available. The approaches of the paper use thesynchronised and accurate measurements from grid monitoring devices located atthe LV distribution grids. It is assumed that the implementation of themethodology is centralised, where a grid monitoring device or a centralplatform is capable to host grid aware algorithms and to communicate controlsetpoints to DERs. The approaches have been validated on a real MV and LVnetworks of a Swiss DSO equipped with grid monitoring devices. The results, interms of technical losses, grid violation costs and flexibility capabilitycurve, show the efficacy of the optimal operation and flexibility estimationmethodologies and therefore, can be easily deployed.
Majumdar A, Alizadeh-Mousavi O, Distribution Grid Robust Operation under Forecast Uncertainties with Flexibility Estimation from Low Voltage Grids using a Monitoring and Control Equipment
Due to increased penetration of renewable resources in the distribution grid,the distribution system operator (DSO) faces increased challenges to maintainsecurity and quality of supply. Since, a large proportion of renewables areintermittent generations, maintaining production and consumption balance of theelectric system is at stake. The DSO needs to procure flexibilities not onlyfrom large resources, but also small-scale resources connected to the LV grid.Therefore, there is a need to estimate the aggregate flexibility at thesecondary substation available from the LV grids. The flexibility estimationcan only be achieved through monitoring of LV grid and the distributed energyresources (DERs) connected at the LV level. Moreover, the variability ofintermittent resources affects the flexibility estimation methodology, and theDSO operation must be robust to the changes in generation or demand outputs.Furthermore, the up-to-date and accurate model of the LV grid is difficult toaccess. This paper demonstrates a methodology of estimating flexibility bysensitivity coefficients and thus, eliminating the need to have an up-to-dateLV grid model. It further presents a robust optimisation based methodology forgrid operation to address the impact of forecast uncertainties associated withthe variable DER output. The methodologies illustrate the value of gridmonitoring with a monitoring equipment. It has been validated on a real networkof a Swiss DSO with several grid monitoring devices.
Majumdar A, Alizadeh-Mousavi O, Efficient distribution grid flexibility provision through model-based MV grid and model-less LV grid approach
In order to maintain security and quality of supply while supportingincreased intermittent generation and electrification of heating and transportat the LV grid, the provision of flexibility in the framework of distributiongrid operation is pivotal. However, the availability of updated and accurate LVgrid model is a challenge for the distribution system operator (DSO). Thispaper demonstrates a methodology of efficient flexibility provision andactivation through a sensitivity coefficients-based model-less LV grid and amodelled MV grid approach. The paper further illustrates the value ofmonitoring and control through a LV DERMS platform for efficient realisation ofthis flexibility provision and activation. The methodology has been tested on areal MV and LV network of a Swiss DSO. The results show that there is areduction of cost of operation for a DSO.
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