arXiv subjects

Di Shi

Publications and source records attributed to Di Shi.

At least 55 records · Page 3Linked to original sources

arXiv2019

Submodular Load Clustering with Robust Principal Component Analysis

Traditional load analysis is facing challenges with the new electricity usage patterns due to demand response as well as increasing deployment of distributed generations, including photovoltaics (PV), electric vehicles (EV), and energy storage systems (ESS). At the transmission system, despite of irregular load behaviors at different areas, highly aggregated load shapes still share similar characteristics. Load clustering is to discover such intrinsic patterns and provide useful information to other load applications, such as load forecasting and load modeling. This paper proposes an efficient submodular load clustering method for transmission-level load areas. Robust principal component analysis (R-PCA) firstly decomposes the annual load profiles into low-rank components and sparse components to extract key features. A novel submodular cluster center selection technique is then applied to determine the optimal cluster centers through constructed similarity graph. Following the selection results, load areas are efficiently assigned to different clusters for further load analysis and applications. Numerical results obtained from PJM load demonstrate the effectiveness of the proposed approach.

cs.LG↗

arXiv2019

Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications

Design of an effective and reliable communication network supporting smart grid applications requires a selection of appropriate communication technologies and protocols. The objective of this paper is to study and quantify the capabilities of an Advanced Metering Infrastructure (AMI) to support the simultaneous operation of major smart grid functions. These include smart metering, price-induced controls, distribution automation, demand response and electric vehicle charging/discharging applications in terms of throughput and latency. OPNET is used to simulate the performance of selected communication technologies and protocols. Research findings indicate that smart grid applications can operate simultaneously by piggybacking on an existing AMI infrastructure and still achieve their latency requirements.

cs.NI↗

arXiv2019

Bayesian Estimation Based Load Modeling Report

This report presents the detailed steps of establishing the composite load model in the power system. The derivations of estimation the ZIP model and IM model parameters are proposed in this report. This is a supplementary material for the paper submitted to PES GM 2019.

math.PR↗

arXiv2018

Optimal Energy Management for Commercial Buildings Considering Comprehensive Comfort Levels in a Retail Electricity Market

Demand response has been implemented by distribution system operators to reduce peak demand and mitigate contingency issues on distribution lines and substations. Specifically, the campus based commercial buildings make the major contributions to peak demand in a distribution system. Note that prior works neglect the consumers comfort level in performing demand response, which limits their applications as the incentives are not worth as compared to the loss in comfort levels for most time. Thus, a framework to comprehensively consider both operating costs and comfort levels is necessary. Moreover, distributed energy resources are widely deployed in commercial buildings such as roof top solar panels, plug in electric vehicles, and energy storage units, which bring various uncertainties to the distribution systems, i.e., output of renewable; electricity prices; arrival and departure of plug-in electric vehicles; business hour demand response signals and flexible energy demand. In this paper, we propose an optimal demand response framework to enable local control of demand-side appliances that are usually too small to participate in a retail electricity market. Several typical small demand side appliances, i.e., heating, ventilation, and air conditioning systems, electric water heaters and plug-in electric vehicles, are considered in our proposed model. Their operations are coordinated by a central controller, whose objective is to minimize the total cost and maximize the customers comfort levels for multiple commercial buildings. A scenario-based stochastic programming is leveraged to handle the aforementioned uncertainties. Numerical results based on the practical data demonstrate the effectiveness of the proposed framework. In addition, the trade off between the operation costs of commercial buildings and customers comfort levels is illustrated.

math.OC↗

arXiv2018

A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation

This paper proposes a resilient-backpropagation-neural-network-(Rprop-NN) based algorithm for Photovoltaic (PV) maximum power point tracking (MPPT). A supervision mechanism is proposed to calibrate the Rprop-NN-MPPT reference and limit short-circuit current caused by incorrect prediction. Conventional MPPT algorithms (e.g., perturb and observe (P&O), hill climbing, and incremental conductance (Inc-Cond) etc.) are trial-and-error-based, which may result in steady-state oscillations and loss of tracking direction under fast-changing ambient environment. In addition, partial shading is also a challenge due to the difficulty of finding the global maximum power point on a multi-peak characteristic curve. As an attempt to address the aforementioned issues, a novel Rprop-NN MPPT algorithm is developed and elaborated in this work. Multiple case studies are carried out to verify the effectiveness of the proposed algorithm.

eess.SP↗

arXiv2018

Optimization of Battery Energy Storage to Improve Power System Oscillation Damping

A placement problem for multiple Battery Energy Storage System (BESS) units is formulated towards power system transient voltage stability enhancement in this paper. The problem is solved by the Cross-Entropy (CE) optimization method. A simulation-based approach is adopted to incorporate higher-order dynamics and nonlinearities of generators and loads. The objective is to maximize the voltage stability index, which is setup based on certain grid-codes. Formulations of the optimization problem are then discussed. Finally, the proposed approach is implemented in MATLAB/DIgSILENT and tested on the New England 39-Bus system. Results indicate that installing BESS units at the optimized location can alleviate transient voltage instability issue compared with the original system with no BESS. The CE placement algorithm is also compared with the classic PSO (Particle Swarm Optimization) method, and its superiority is demonstrated in terms of a faster convergence rate with matched solution qualities.

eess.SY↗

arXiv2018

Small-signal Stability Analysis and Performance Evaluation of Microgrids under Distributed Control

Distributed control, as a potential solution to decreasing communication demands in microgrids, has drawn much attention in recent years. Advantages of distributed control have been extensively discussed, while its impacts on microgrid performance and stability, especially in the case of communication latency, have not been explicitly studied or fully understood yet. This paper addresses this gap by proposing a generalized theoretical framework for small-signal stability analysis and performance evaluation for microgrids using distributed control. The proposed framework synthesizes generator and load frequency-domain characteristics, primary and secondary control loops, as well as the communication latency into a frequency-domain representation which is further evaluated by the generalized Nyquist theorem. In addition, various parameters and their impacts on microgrid dynamic performance are investigated and summarized into guidelines to help better design the system. Case studies demonstrate the effectiveness of the proposed approach.

eess.SY↗

arXiv2018

Model Predictive Control of H5 Inverter for Transformerless PV Systems with Maximum Power Point Tracking and Leakage Current Reduction

Transformerless grid-connected solar photovoltaic (PV) systems have given rise to more research and commercial interests due to their multiple merits, e.g., low leakage current and small size. In this paper, a model-predictive-control (MPC)-based strategy for controlling transformerless H5 inverter for single-phase PV distributed generation system is proposed. The method further reduces the PV leakage current in a cost-effective and safe manner and it shows a satisfactory fault-ride-through capability. Moreover, for the first of its kind, PV maximum power point tracking is implemented in the single-stage H5 inverter using MPC-based controllers. Various case studies are carried out, which provide the result comparisons between the proposed and conventional control methods and verify the promising performance of the proposed method.

math.OC↗

arXiv2018

Optimal Allocation of Series FACTS Devices Under High Penetration of Wind Power Within a Market Environment

Series FACTS devices are one of the key enablers for very high penetration of renewables due to their capabilities in continuously controlling power flows on transmission lines. This paper proposes a bilevel optimization model to optimally locate variable series reactor (VSR) and phase shifting transformer (PST) in the transmission network considering high penetration of wind power. The upper level problem seeks to minimize the \textcolor{black}{investment cost} on series FACTS, the cost of wind power curtailment and possible load shedding. The lower level problems capture the market clearing under different operating scenarios. Due to the poor scalability of $Bθ$ formulation, the \textsl{shift factor} structure of FACTS allocation is derived. A customized reformulation and decomposition algorithm is designed and implemented to solve the proposed bilevel model with binary variables in both upper and lower levels. Detailed numerical results based on 118-bus system demonstrate the efficient performance of the proposed planning model and the important role of series FACTS for facilitating the integration of wind power.

math.OC↗

arXiv2018

Sensitivity Based Thevenin Index for Voltage Stability Assessment Considering N-1 Contingency

This paper proposes an approach to address the voltage stability assessment (VSA) considering N-1 contingency. The approach leverages the sensitivity based Thevenin index (STI) which involves evaluating the Jacobian matrix at current operating condition. Since the N-1 contingency case is hypothetical, there is no information regarding the operating condition after a foreseen contingency. The proposed approach first estimates the post-contingency operating point as well as possible PV-PQ transitions based on the current operating point. Then the STI for each contingency can be predicted using the estimated operating condition. Numerical results based on IEEE 14-bus system demonstrate the accuracy of the proposed approach in predicting the voltage stability margin under contingency. Moreover, the on-line implementation of the proposed approach is promising since it only involves solving several linear equations.

math.OC↗

arXiv2018

Optimal Distributed Energy Resources Sizing for Commercial Building Hybrid Microgrids

As microgrids have advanced from early prototypes to relatively mature technologies, converting data center integrated commercial buildings to microgrids provides economic, reliability and resiliency enhancements for the building owners. Thus, microgrid design and economically sizing distributed energy resources (DER) are becoming more demanding to gain widespread microgrids commercial viability. In this paper, an optimal DER sizing formulation for a hybrid AC/DC microgrid configuration has been proposed to leverage all benefits that AC or DC microgrid could solely contribute. Energy storage (ES), photovoltaics (PV) and power electronics devices are coordinately sized for economic grid-connected and reliable islanded operations. Time-of-use (TOU) energy usages charges and peak demand charges are explicitly modeled to achieve maximum level of cost savings. Numerical results obtained from a real commercial building load demonstrate the benefits of the proposed approach and the importance of jointly sizing DER for the grid-connected and islanded modes.

math.OC↗

arXiv2018

A Robust Power Grid Defense Model Considering Load Demand and Wind Generation Uncertainties

It is a major task to develop effective strategies for defending the power system against deliberate attacks. It is critical to comprehensively consider the human-related and environmental risks and uncertainties, which is missing in existing literature. This paper considers the load demand uncertainties and wind generation uncertainties in addition to the interactive attacker/defender behaviors. Specifically, a defender-attacker-nature-operator model is proposed, which incorporates the attack/defense interaction, the corrective re-dispatch of the operator, the coordination between the attack strategy and the stochastic nature of load demands and wind generations. The Column-and-Constraint Generation (C&CG) algorithm is adopted for solving the proposed model by decomposing the proposed model into a master problem and a sub-problem. Simulations are performed using MATLAB and CPLEX on a modified IEEE RTS79 system. The simulation results verify the validity of the proposed model.

math.OC↗

arXiv2018

Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining the optimal control action before switching signals are sent. The proposed algorithm eliminates the needs of PI, PWM, and droop components, and offers 1) accurate PV maximum power point tracking (MPPT) and battery charging/discharging control, 2) DC and multiple AC bus voltage/frequency regulation, 3) a precise power sharing scheme among DERs without voltage or frequency deviation, and 4) a unified MPC design flow for hybrid microgrids. Multiple case studies are carried out, which verify the satisfactory performance of the proposed method.

math.OC↗

arXiv2017

The Allocation of a Variable Series Reactor Considering AC Constraints and Contingencies

The Variable Series Reactors (VSRs) can efficiently control the power flow through the adjustment of the line reactance. When they are appropriately allocated in the power network, the transmission congestion and generation cost can be reduced. This paper proposes a planning model to optimally allocate VSRs considering AC constraints and multi-scenarios including base case and contingencies. The planning model is originally a non-convex large scale mixed integer nonlinear program (MINLP), which is generally intractable. The proposed Benders approach decomposes the MINLP model into a mixed integer linear program (MILP) master problem and a number of nonlinear subproblems. Numerical case studies based on IEEE 118-bus demonstrate the high performance of the proposed approach.

math.OC↗

arXiv2017

Recover the lost Phasor Measurement Unit Data Using Alternating Direction Multipliers Method

This paper presents a novel algorithm for recovering missing data of phasor measurement units (PMUs). Due to the low-rank property of PMU data, missing measurement recovery can be formulated as a low-rank matrix-completion problem. Based on maximum-margin matrix factorization, we propose an efficient algorithm based on alternating direction method of multipliers (ADMM) for solving the matrix completion problem. Comparing to existing approaches, the proposed ADMM based algorithm does not need to estimate the rank of the target data matrix and provides better performance in computation complexity. In addition, we consider the case of measurements missing from all PMU channels and provide a strategy of reshaping the matrix which contains the received PMU data for recovery. Numerical results using PMU measurements from IEEE 68-bus power system model illustrate the effectiveness and efficiency of the proposed approaches.

math.NA↗

arXiv2017

Forced Oscillation Source Location via Multivariate Time Series Classification

Precisely locating low-frequency oscillation sources is the prerequisite of suppressing sustained oscillation, which is an essential guarantee for the secure and stable operation of power grids. Using synchrophasor measurements, a machine learning method is proposed to locate the source of forced oscillation in power systems. Rotor angle and active power of each power plant are utilized to construct multivariate time series (MTS). Applying Mahalanobis distance metric and dynamic time warping, the distance between MTS with different phases or lengths can be appropriately measured. The obtained distance metric, representing characteristics during the transient phase of forced oscillation under different disturbance sources, is used for offline classifier training and online matching to locate the disturbance source. Simulation results using the four-machine two-area system and IEEE 39-bus system indicate that the proposed location method can identify the power system forced oscillation source online with high accuracy.

eess.SP↗

arXiv2017

An Extended Kalman Filter Enhanced Hilbert-Huang Transform in Oscillation Detection

Hilbert-Huang transform (HHT) has drawn great attention in power system analysis due to its capability to deal with dynamic signal and provide instantaneous characteristics such as frequency, damping, and amplitudes. However, its shortcomings, including mode mixing and end effects, are as significant as its advantages. A preliminary result of an extended Kalman filter (EKF) method to enhance HHT and hopefully to overcome these disadvantages is presented in this paper. The proposal first removes dynamic DC components in signals using empirical mode decomposition. Then an EKF model is applied to extract instant coefficients. Numerical results using simulated and real-world low-frequency oscillation data suggest the proposal can help to overcome the mode mixing and end effects with a properly chosen number of modes.

eess.SP↗

arXiv2017

Online Coherence Identification Using Dynamic Time Warping for Controlled Islanding

Controlled islanding is considered to be the last countermeasure to prevent system-wide blackouts in case of cascading failures. It splits the system into self-sustained islands to maintain transient stability at the expense of possible loss of load. Generator coherence identification is critical to controlled islanding scheme as it helps identify the optimal cut-set to maintain system transient stability. This paper presents a novel approach for online generator coherency identification using phasor measurement unit (PMU) data and dynamic time warping (DTW). Results from the coherence identification are used to further cluster non-generator buses using spectral clustering with the objective of minimizing power flow disruption. The proposed approach is validated and compared to existing methods on the IEEE 39-bus system, through which its advantages are demonstrated.

eess.SY↗