skip to main content

This content will become publicly available on November 14, 2022

Title: Implementation of CVR in Distribution Networks by Optimal Coordination of BESS and PV Inverters Using Arithmetic Optimization Algorithm
This article proposes a new framework for the substation demand reduction and power loss minimization in distribution networks by implementing conservation voltage reduction (CVR) strategy. The proposed framework coordinates Battery Energy Storage Systems (BESS), Smart PV inverters and voltage control devices -including OLTC and voltage regulators- so that the substation demand and network power loss are reduced while the service voltage range meets the IEEE 1547 standard (120-114 V). The suggested CVR strategy is applied to the IEEE 34-bus case study system consisting of two PV generations and BESS. The smart PV inverters are controlled based on the combined Volt/VArVolt/Watt (VVW) characteristics scheme. Also, BESS is charged and discharged with regard to the time and peaks have control modes, respectively. The Arithmetic Optimization Algorithm (AOA) is implemented in MATLAB scripts for solving the optimization problem. Power flow studies are carried out using OpenDSS software. Results reveal that the new framework can achieve higher substation demand reduction considering the concurrent control of PVs and BESS.
Authors:
;
Award ID(s):
1939144
Publication Date:
NSF-PAR ID:
10317607
Journal Name:
IEEE Green Technologies Conference (GreenTech)
Sponsoring Org:
National Science Foundation
More Like this
  1. Voltage instability occurs when a power system is unable to meet reactive power demand at one or more buses. Voltage instability events have caused several major outages and promise to become more frequent due to increasing energy demand. The future smart grid may help to ensure voltage stability by enabling rapid detection of possible voltage instability and implementation of corrective action. These corrective actions will only be effective in restoring stability if they are chosen in a timely, scalable manner. Current techniques for selecting control actions, however, rely on exhaustive search, and hence may choose an inefficient control strategy. In this paper, we propose a submodular optimization approach to designing a control strategy to prevent voltage instability at one or more buses. Our key insight is that the deviation from the desired voltage is a supermodular function of the set of reactive power injections that are employed, leading to computationally efficient control algorithms with provable optimality guarantees. Furthermore, we show that the optimality bound of our approach can be improved from 1/3 to 1/2 when the power system operates under heavy loading conditions. We demonstrate our framework through extensive simulation study on the IEEE 30 bus test case.
  2. The fast-growing installation of solar PVs has a significant impact on the operation of distribution systems. Grid-tied solar inverters provide reactive power capability to support the voltage profile in a distribution system. In comparison with traditional inverters, smart inverters have the capability of real time remote control through digital communication interfaces. However, cyberattack has become a major threat with the deployment of Information and Communications Technology (ICT) in a smart grid. The past cyberattack incidents have demonstrated how attackers can sabotage a power grid through digital communication systems. In the worst case, numerous electricity consumers can experience a major and extended power outage. Unfortunately, tracking techniques are not efficient for today’s advanced communication networks. Therefore, a reliable cyber protection system is a necessary defense tool for the power grid. In this paper, a signature-based Intrusion Detection System (IDS) is developed to detect cyber intrusions of a distribution system with a high level penetration of solar energy. To identify cyberattack events, an attack table is constructed based on the Temporal Failure Propagation Graph (TFPG) technique. It includes the information of potential cyberattack patterns in terms of attack types and time sequence of anomaly events. Once the detected anomaly events are matchedmore »with any of the predefined attack patterns, it is judged to be a cyberattack. Since the attack patterns are distinguishable from other system failures, it reduces the false positive rate. To study the impact of cyberattacks on solar devices and validate the performance of the proposed IDS, a realistic Cyber-Physical System (CPS) simulation environment available at Virginia Tech (VT) is used to develop an interconnection between the cyber and power system models. The CPS model demonstrates how communication system anomalies can impact the physical system. The results of two example cyberattack test cases are obtained with the IEEE 13 node test feeder system and the power system simulator, DIgSILENT PowerFactory.« less
  3. This paper proposes a strategy to control a group of thermostatically controlled loads (TCLs) such that the variability in their aggregate load is reduced. This strategy could be deployed in areas of a distribution network that experience voltage excursions due to net load fluctuations, such as areas with high penetrations of photovoltaic (PV) generation and/or electric vehicles (EVs), We limit variation in the power consumption of a group of TCLs using a control strategy previously developed for large aggregations of switched systems. Using this strategy, we constrain the number of TCLs that are on (i.e., actively consuming power) between upper and lower bounds. In simulations, the control strategy successfully decreases the range over which TCL power consumption varies. Percent reductions in range are greatest for medium group sizes: we find a median reduction of 82% for groups of 50 TCLs, 74% for groups of 1000 TCLs, and 59% for groups of 5 TCLs. Reducing the variability of a distribution network's power injections helps to reduce voltage variability. In a simulation of a distribution line supplying 25 households, half with PV systems, the control strategy reduces the total range of voltage by 0.02 p.u. and prevents a violation of the 0.95more »p.u. limit. Lastly, we propose a new control strategy for a more realistic TCL model that includes compressor lockout. The new strategy performs comparably to the original strategy and is demonstrated through simulation.« less
  4. Photovoltaic (PV) array analytics and control have become necessary for remote solar farms and for intelligent fault detection and power optimization. The management of a PV array requires auxiliary electronics that are attached to each solar panel. A collaborative industry-university-government project was established to create a smart monitoring device (SMD) and establish associated algorithms and software for fault detection and solar array management. First generation smart monitoring devices (SMDs) were built in Japan. At the same time, Arizona State University initiated research in algorithms and software to monitor and control individual solar panels. Second generation SMDs were developed later and included sensors for monitoring voltage, current, temperature, and irradiance at each individual panel. The latest SMDs include a radio and relays which allow modifying solar array connection topologies. With each panel equipped with such a sophisticated SMD, solar panels in a PV array behave essentially as nodes in an Internet of Things (IoT) type of topology. This solar energy IoT system is currently programmable and can: a) provide mobile analytics, b) enable solar farm control, c) detect and remedy faults, d) optimize power under different shading conditions, and e) reduce inverter transients. A series of federal and industry grants sponsoredmore »research on statistical signal analysis, communications, and optimization of this system. A Cyber-Physical project, whose aim is to improve solar array efficiency and robustness using new machine learning and imaging methods, was launched recently« less
  5. Uwe Sauer, Dirk (Ed.)
    A B S T R A C T The probabilistic and intermittent output power of Wind Turbines (WT) is one major inconsistency of these Renewable Energy Sources (RES). Battery Energy Storage Systems (BESS) are a suitable solution to mitigate this intermittency by smoothening WT’s output power. Although the main benefit of BESSs mentions as peak shaving and load-shifting, but in this research, it will verify that optimal placement and sizing them jointly with WTs can lead to more benefits like compensating the required system’s reactive power support from WTs. The reactive power size of WTs and BESSs will be derived from the result of the joint sizing and placement in this study, as well as their active power output to meet the load demand. This can facilitate WTs and BESSs contribution to cover the system’s required reactive power and their participation in the reactive power market and ancillary services. This paper also proposes new cost functions for both WTs and BESSs and minimizes their cost while ensuring minimal total loss (active and reactive) in the power distribution system. This can benefit both WTs’ and BESSs’ owners as well as system operators. Suitable placement and sizing of the WTs and BESSsmore »can also improve the load bus voltage profiles, which can benefit the end-users, and will verify using the proposed optimization by different case studies on the 33 bus distribution system. The results of case studies ascertain the consistency of the proposed formulation for placement and sizing BESSs and WTs jointly, as well as other benefits to the power system, the power plant owners, and system operators.« less