Distribution System Voltage Management and Optimization for Integration of Renewables and Electric Vehicles: Research Gap Analysis

California is striving to achieve 33% renewable penetration by 2020 in accordance with the state’s Renewable Portfolio Standard (RPS). The behavior of renewable resources and electric vehicles in distribution systems is creating constraints on the penetration of these resources into the distribution system. One such constraint is the ability of present-­‐‑day voltage management methodologies to maintain proper distribution system voltage profiles in the face of higher penetrations of PV and electric vehicle technologies. This white paper describes the research gaps that have been identified in current Volt/VAR Optimization and Control (VVOC) technologies, the emerging technologies which are becoming available for use in VVOC, and the research gaps which exist and must be overcome in order to realize the full promise of these emerging technologies

The Combined Effect of Photovoltaic and Electric Vehicle Penetration on Conservation Voltage Reduction in Distribution System

Global conditions over the past dozen years have led to an expanded appetite for renewable energy sources: The diminishing fossil fuel supply, the political instability of countries producing these fossil fuels, the ever-more destructive effects of global warming, and the lowering of costs for renewable energy technologies have made countries around the world reconsider their sources of energy. The proliferation of photovoltaic (PV) systems especially has surged dramatically with the decreasing initial costs for installation, and increasing government support in the form of renewable energy portfolios, feed-in-tariffs, tax incentives, etc. Furthermore, electric vehicles (EV) are also becoming widespread due to recent advances in battery and electric drive technologies, and the desperate need to reduce air pollution in urban areas. Meanwhile, electric utilities are always making an effort to run their system more efficiently by encouraging the use of energy-efficient appliances and customer participation in demand-side management programs. In an attempt to further reduce load demand; many utilities regulate the voltage along their distribution feeders in a particular way that is referred to as conservation voltage reduction (CVR). The key principle of CVR operation is that the ANSI standard voltage band between 114 and 126 volts can be compressed via regulation to the lower half (114–120) instead of the upper half (120–126), producing measurable energy savings at low cost and without harm to consumer appliances. As the penetration of distributed PV and EV charging station increases, this can dramatically change the conventional demand profile as PV system act as negative loads during the daylight hours, and EVs significantly increase load demand during charging. Consequently, traditional means of controlling the voltage by capacitor switching and voltage regulators can be improved in this “smart” grid era by adding a fleet of enabling devices including the smart PV inverter functionalities, such as Volt/VAR control, and intelligent EV charging schemes. This thesis explores how better energy conservation is achieved by CVR in a modern distribution system with advanced distributed PV systems inverters and EV loads. Then it summarizes computer simulations that are conducted on the IEEE 37 and IEEE 123 node test feeders using OpenDSS interfaced with MATLAB

Dynamic Analysis of a Microgrid Powered With an Inverter and Machine-Based Distributed Resources

The proliferation of renewable distributed energy resources, particularly photovoltaic (PV) power systems, and the increasing need for a reliable power supply has led to the concept of microgrids, a mini-grid that consists of locally connected power generation units and needs, able to operate connected or disconnected from the utility grid, using controlled and coordinated methods to provide for the users of the microgrid the best possible conditions for their needs. The main technical issues facing microgrids include some of the following, seamless transition from stand-alone to utility grid connected operation, how to preserve frequency and voltage stability, and provide the lowest cost power among numerous power resources. Technologies that will be used in the future smart grid will be built, tested, and fielded in modern microgrids with many national laboratories, utility companies, and universities using microgrids of all different types for research and development. This dissertation describes the design, fabrication, and testing of a microgrid facility which comprises adjustable resistive and inductive loads, a diesel-powered generator (DG), an advanced inverter PV system, a battery energy storage system (BESS), monitoring, protection, and control devices. The microgrid facility was built with the foresight that it would be used for conducting tests and experiments related to microgrid technical challenges, thus ease of access and expandability were built in which allows it to be used for both research and education purposes. Numerous experimental tests conducted include the following: (a) the dynamic response of a DG to load changes, (b) an advanced PV inverters autonomous functions, (c) advanced inverter islanding test, (d) load sharing among the DG and PV system, (e) PV and battery storage systems load sharing, (d) dynamic performance of an advanced PV inverter and a DG during unintentional islanding under different power export/import conditions, and (e) BESS iv response to utility outage under different PV operating conditions. Attempts to improve reliability and power quality are made by expanding the PV inverter ride-through times during frequency and voltage abnormalities. An economic analysis in terms of Net Present Value (NPV) is conducted on a residential application where a BESS is paired with a PV system to shift solar energy in favor Time-of-Use (ToU) pricing and to provide ancillary grid services

Evolution of the Electricity Distribution Networks : Active Management Architecture Schemes and Microgrid Control Functionalities

The power system transition to smart grids brings challenges to electricity distribution network development since it involves several stakeholders and actors whose needs must be met to be successful for the electricity network upgrade. The technological challenges arise mainly from the various distributed energy resources (DERs) integration and use and network optimization and security. End-customers play a central role in future network operations. Understanding the network’s evolution through possible network operational scenarios could create a dedicated and reliable roadmap for the various stakeholders’ use. This paper presents a method to develop the evolving operational scenarios and related management schemes, including microgrid control functionalities, and analyzes the evolution of electricity distribution networks considering medium and low voltage grids. The analysis consists of the dynamic descriptions of network operations and the static illustrations of the relationships among classified actors. The method and analysis use an object-oriented and standardized software modeling language, the unified modeling language (UML). Operational descriptions for the four evolution phases of electricity distribution networks are defined and analyzed by Enterprise Architect, a UML tool. This analysis is followed by the active management architecture schemes with the microgrid control functionalities. The graphical models and analysis generated can be used for scenario building in roadmap development, real-time simulations, and management system development. The developed method, presented with high-level use cases (HL-UCs), can be further used to develop and analyze several parallel running control algorithms for DERs providing ancillary services (ASs) in the evolving electricity distribution networks.© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Evaluation of conservation voltage regulation techniques in microgrids

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáThis work has the main objective to present an evaluation of the Conservation Voltage Regulation (CVR) technique applied to a small microgrid based on renewable energy sources. Conservation Voltage Regulation (CVR) is based on the premise that reduction of the supplier voltage will lead to reduced energy consumption by final consumers without harming their appliances. CVR implementation is one of the cheapest technologies that can be used to provide better resources utilization, demand reduction and efficiency improvement, being this principle already validatedão when applied in public networks. The actual trend of Distributed Generation based on Renewable Energy Sources in distribution systems also impacts on voltage control and on CVR schemes. By this way, it is important to analyze the impact of CVR in microgrids. Experimental tests have been performed on a demonstration project of a small microgrid of the Polytechnic Institute of Bragança in order to evaluate CVR benefits. Voltage and frequency control strategies involved in this kind of networks are conceptually similar to the ones existing in the public network, but due to intermittency of renewable sources, control dynamics is completely different, with consequences in the application and evaluation of CVR technique. The energy consumption varies with voltage and also with frequency, which do not allow the translation of CVR advantages and evaluation techniques already validated in public networks to small microgrids.Este trabalho tem o objetivo principal de apresentar uma avaliação da técnica de “Conservation Voltage Regulation” (CVR) aplicada a uma pequena microrrede baseada em fontes de energia renováveis. O CVR baseia-se na premissa de que a redução da tensão do fornecedor levará ao consumo de energia reduzido pelos consumidores finais sem prejudicar seus aparelhos. A implementação da CVR é uma das tecnologias mais baratas que podem ser utilizadas para proporcionar uma melhor utilização dos recursos, redução da demanda e melhoria da eficiência, sendo este princípio já validado quando aplicado em redes públicas. A tendência atual da Geração Distribuída baseada em Fontes de Energia Renovável em sistemas de distribuição também afeta o controle de voltagem e os esquemas CVR. Desta forma, é importante analisar o impacto da CVR em microrrede. Testes experimentais foram realizados em um projeto de demonstração de uma pequena microrrede do Instituto Politécnico de Bragança para avaliar benefícios CVR. As estratégias de controle de voltagem e frequência envolvidas neste tipo de redes são conceitualmente semelhantes às existentes na rede pública, mas devido à intermitência de fontes renováveis, a dinâmica de controle é completamente diferente, com consequências na aplicação e avaliação da técnica CVR. O consumo de energia varia com a tensão e também com a frequência, o que não permite a tradução de vantagens de CVR e técnicas de avaliação já validadas em redes públicas para microrrede pequenas

Deep Reinforcement Learning for Distribution Network Operation and Electricity Market

The conventional distribution network and electricity market operation have become challenging under complicated network operating conditions, due to emerging distributed electricity generations, coupled energy networks, and new market behaviours. These challenges include increasing dynamics and stochastics, and vast problem dimensions such as control points, measurements, and multiple objectives, etc. Previously the optimization models were often formulated as conventional programming problems and then solved mathematically, which could now become highly time-consuming or sometimes infeasible. On the other hand, with the recent advancement of artificial intelligence technologies, deep reinforcement learning (DRL) algorithms have demonstrated their excellent performances in various control and optimization fields. This indicates a potential alternative to address these challenges. In this thesis, DRL-based solutions for distribution network operation and electricity market have been investigated and proposed. Firstly, a DRL-based methodology is proposed for Volt/Var Control (VVC) optimization in a large distribution network, to effectively control bus voltages and reduce network power losses. Further, this thesis proposes a multi-agent (MA)DRL-based methodology under a complex regional coordinated VVC framework, and it can address spatial and temporal uncertainties. The DRL algorithm is also improved to adapt to the applications. Then, an integrated energy and heating systems (IEHS) optimization problem is solved by a MADRL-based methodology, where conventionally this could only be solved by simplifications or iterations. Beyond the applications in distribution network operation, a new electricity market service pricing method based on a DRL algorithm is also proposed. This DRL-based method has demonstrated good performance in this virtual storage rental service pricing problem, whereas this bi-level problem could hardly be solved directly due to a non-convex and non-continuous lower-level problem. These proposed methods have demonstrated advantageous performances under comprehensive case studies, and numerical simulation results have validated the effectiveness and high efficiency under different sophisticated operation conditions, solution robustness against temporal and spatial uncertainties, and optimality under large problem dimensions

Coordinated Optimal Voltage Control in Distribution Networks with Data-Driven Methods

Voltage control is facing significant challenges with the increasing integration of photovoltaic (PV) systems and electric vehicles (EVs) in active distribution networks. This is leading to major transformations of control schemes that require more sophisticated coordination between different voltage regulation devices in different timescales. Except for conventional Volt/Var control (VVC) devices such on-load tap change (OLTC) and capacitor banks (CBs), inverter-based PVs are encouraged to participate in voltage regulation considering their flexible reactive power regulation capability. With the vehicle to grid (V2G) technology and inverter-based interface at charging stations, the charging power of an EV can be also controlled to support voltages. These emerging technologies facilitate the development of two-stage coordinated optimal voltage control schemes. However, these new control schemes pursue a fast response speed with local control strategies in shorter snapshots, which fails to track the optimal solutions for the distribution system operation. The voltage control methods mainly aim to mitigate voltage violations and reduce network power loss, but they seldom focus on satisfying the various requirements of PV and EV customers. This may discourage customer-owned resources from participating in ancillary services such as voltage regulation. Moreover, model-based voltage control methods highly rely on the accurate knowledge of power system models and parameters, which is sometimes difficult to obtain in real-life distribution networks. The goal of this thesis is to propose a data-driven two-stage voltage control framework to fill the research gaps mentioned above, showing what frameworks, models and solution methods can be used in the optimal voltage control of modern active distribution systems to tackle the security and economic challenges posed by high integration of PVs and EVs