Real-time coordinated voltage control of PV inverters and energy storage for weak networks with high PV penetration

There are more large-scale PV plants being established in rural areas due to availability of low priced land. However, distribution grids in such areas traditionally have feeders with low X/R ratios, which makes the independent reactive power compensation method less effective on voltage regulation. Consequently, upstream Step Voltage Regulator (SVR) may suffer from excessive tap operations with PV induced fast voltage fluctuations. Although a battery energy storage system (BESS) can successfully smooth PV generation, frequent charge/discharge will substantially affect its cost effectiveness. In this paper, a real-time method is designed to coordinate PV inverters and BESS for voltage regulation. To keep up with fast fluctuations of PV power, this method will be executed in each 5s control cycle. In addition, charging/discharging power of BESS is adaptively retuned by an active adjustment method in order to avoid BESS premature energy exhaustion in a long run. Finally, through a voltage margin control scheme, the upstream SVR and downstream PV inverters and BESS are coordinated for voltage regulation without any communication. This research is validated via an RTDS-MatLab co-simulation platform, and it will provide valuable insights and applicable strategies to both utilities and PV owners for large-scale PV farm integration into rural networks

Voltage Control in Low-Voltage Grids Using Distributed Photovoltaic Converters and Centralized Devices

This paper studies the application of distributed and centralized solutions for voltage control in low voltage (LV) grids with high photovoltaic (PV) penetration. In traditional LV grids, the coordination of distributed PV converters and a centralized device would require massive investments in new communication and control infrastructures. The alternative of exploiting distributed PV converters for voltage control is discussed, showing that it can help to stabilize the voltage in the grid connection points also without coordination between them and/or with a centralized unit. The goal of this paper is to investigate how the setup of the voltage controllers inside PV inverters affects the operation of these controllers taking into account the limits for reactive power injection. In addition, the interaction of distributed PV converters with centralized devices (static var compensators and on load tap changers) is analyzed to assess whether additional benefits may come in these cases

Implementation and assessment of demand response and voltage/var control with distributed generators

The main topic of this research is the efficient operation of a modernized distribution grid from both the customer side and utility side. For the customer side, this dissertation discusses the planning and operation of a customer with multiple demand response programs, energy storage systems and distributed generators; for the utility side, this dissertation addresses the implementation and assessment of voltage/VAR control and conservation voltage reduction in a distribution grid with distributed generators. The objectives of this research are as follows: (1) to develop methods to assist customers to select appropriate demand response programs considering the integration of energy storage systems and DGs, and perform corresponding energy management including dispatches of loads, energy storage systems, and DGs; (2) to develop stochastic voltage/VAR control techniques for distribution grids with renewable DGs; (3) to develop optimization and validation methods for the planning of integration of renewable DGs to assist the implementation of voltage/VAR control; and (4) to develop techniques to assess load-reduction effects of voltage/VAR control and conservation voltage reduction. In this dissertation, a two-stage co-optimization method for the planning and energy management of a customer with demand response programs is proposed. The first level is to optimally select suitable demand response programs to join and integrate batteries, and the second level is to schedule the dispatches of loads, batteries and fossil-fired backup generators. The proposed method considers various demand response programs, demand scenarios and customer types. It can provide guidance to a customer to make the most beneficial decisions in an electricity market with multiple demand response programs. For the implementation of voltage/VAR control, this dissertation proposes a stochastic rolling horizon optimization-based method to conduct optimal dispatches of voltage/VAR control devices such as on-load tap changers and capacitor banks. The uncertainties of renewable DG output are taken into account by the stochastic formulation and the generated scenarios. The exponential load models are applied to capture the load behaviors of various types of customers. A new method to simultaneously consider the integration of DGs and the implementation of voltage/VAR control is also developed. The proposed method includes both solution and validation stages. The planning problem is formulated as a bi-level stochastic program. The solution stage is based on sample average approximation (SAA), and the validation stage is based on multiple replication procedure (MRP) to test the robustness of the sample average approximation solutions of the stochastic program. This research applies big data-driven analytics and load modeling techniques to propose two novel methodologies to assess the load-reduction effects of conservation voltage reduction. The proposed methods can be used to assist utilities to select preferable feeders to implement conservation voltage reduction.Ph.D

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

Planning and Management of a solar power-based distribution system

This thesis is aimed at the response of the power system network to the integration of solar photovoltaic (PV) generation and battery energy storage systems (BESS). Any solar power–based system integrated into a grid has voltage fluctuations that must be controlled through adaptive and robust control algorithms. The siting of battery in a distribution system affects system performance, including voltage regulation, system losses and cost minimization. In particular, here the aim is to analyse how the present-day schemes and technologies affect voltages, and their control, in the network. Another focus is on the optimal placement of BESS to facilitate system loss minimisation and cost reduction in the system. The battery placement optimisation is achieved through the minimisation of the losses in, and the cost of, the system. The voltage regulation is achieved through two control algorithms: Synchronous Reference Frame theory (SRFT) and adaptive linear neural network (ADALINE), which are subsequently modified by incorporation of fuzzy logic into the control system. Both battery placement optimisation and improvements to voltage regulation are shown to improve performance of the system. A further aim of this work is to improve cooperation between present day grid regulation equipment and schemes and the conventional methods through advancements in the control techniques. The aims of this thesis are as follows: 1. It is essential to place BESSs optimally. The aim of the thesis is to study and enhance the method of the optimal siting of battery energy storage in the presence of renewable energy–based power generating sources (RES)– such as solar PV – in a low-voltage power system network. A model for optimisation is developed to potentially find the battery site that enhances the hosting capability of the RES of the power system network. Among the essential points of this technique are its accuracy and robust nature. The fitness function includes the minimisation of the cost of operation and of system losses. 2. The second research objective is to examine the power control techniques of the inverter that might be leading to the voltage quality issues during unbalanced voltage scenarios, especially with solar PV–based generation in the power system. As such, after the implementation of the suggested coordination of the control mechanism into the grid under study, the variations in the voltage due to the solar PV variability dynamics are regulated more quickly and more precisely compared with the control schemes employed in the past. This substantially minimises the voltage fluctuations in time and amplitude, helps in mitigating hunting phenomena in voltage and provides alternative to the unnecessary control operations existing in the system