Local Storage Meets Local Demand: A Technical Solution to Future Power Distribution System

Future power systems are expected to integrate large-scale stochastic and intermittent generation and load due to reduced use of fossil fuel resources, including renewable energy sources (RES) and electric vehicles (EV). Inclusion of such resources poses challenges for the dynamic stability of synchronous transmission and distribution networks, not least in terms of generation where system inertia may not be wholly governed by large-scale generation but displaced by small-scale and localised generation. Energy storage systems (ESS) can limit the impact of dispersed and distributed generation by offering supporting reserve while accommodating large-scale EV connection; the latter (load) also participating in storage provision. In this paper, a local energy storage system (LESS) is proposed. The structure, requirement and optimal sizing of the LESS are discussed. Three operating modes are detailed, including: 1) storage pack management; 2) normal operation; and 3) contingency operation. The proposed LESS scheme is evaluated using simulation studies based on data obtained from the Northern Ireland regional and residential network.

AUTONOMOUS POWER DISTRIBUTION SYSTEMS

Using robotic systems for many missions that require power distribution can decrease the need for human intervention in such missions significantly. For accomplishing this capability a robotic system capable of autonomous navigation, power systems adaptation, and establishing physical connection needs to be developed. This thesis presents developed path planning and navigation algorithms for an autonomous ground power distribution system. In this work, a survey on existing path planning methods along with two developed algorithms by author is presented. One of these algorithms is a simple path planner suitable for implementation on lab-size platforms. A navigation hierarchy is developed for experimental validation of the path planner and proof of concept for autonomous ground power distribution system in lab environment. The second algorithm is a robust path planner developed for real-size implementation based on lessons learned from lab-size experiments. The simulation results illustrates that the algorithm is efficient and reliable in unknown environments. Future plans for developing intelligent power electronics and integrating them with robotic systems is presented. The ultimate goal is to create a power distribution system capable of regulating power flow at a desired voltage and frequency adaptable to load demands.

A model predictive approach for community battery energy storage system optimization

This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.

Coordinated control of grid connected photovoltaic reactive power and battery energy storage systems to improve the voltage profile of a residential distribution feeder

Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

Optimization and Control of Power Flow in Distribution Networks

Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale adoption of residential and commercial solar photovoltaics (PV) plants is completely changing the traditional slowly-varying unidirectional power flow nature of distribution systems. High share of intermittent renewables pose several technical challenges, including voltage and frequency control. But along with these challenges, renewable generators also bring with them millions of new DC-AC inverter controllers each year. These fast power electronic devices can provide an unprecedented opportunity to increase energy efficiency and improve power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power flow optimization and control methods that achieve system-wide efficiency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable generators.

Proposed solutions to power flow control problems in the literature range from fully centralized to fully local ones. In this thesis, we will focus on the two ends of this spectrum. In the first half of this thesis (chapters 2 and 3), we seek optimal solutions to voltage control problems provided a centralized architecture with complete information. These solutions are particularly important for better understanding the overall system behavior and can serve as a benchmark to compare the performance of other control methods against. To this end, we first propose a branch flow model (BFM) for the analysis and optimization of radial and meshed networks. This model leads to a new approach to solve optimal power flow (OPF) problems using a two step relaxation procedure, which has proven to be both reliable and computationally efficient in dealing with the non-convexity of power flow equations in radial and weakly-meshed distribution networks. We will then apply the results to fast time- scale inverter var control problem and evaluate the performance on real-world circuits in Southern California Edison’s service territory.

The second half (chapters 4 and 5), however, is dedicated to study local control approaches, as they are the only options available for immediate implementation on today’s distribution networks that lack sufficient monitoring and communication infrastructure. In particular, we will follow a reverse and forward engineering approach to study the recently proposed piecewise linear volt/var control curves. It is the aim of this dissertation to tackle some key problems in these two areas and contribute by providing rigorous theoretical basis for future work.

Performance comparison of VSC-based shunt and series compensators used for load voltage control in distribution systems

In this paper, the performance of voltage-source converter-based shunt and series compensators used for load voltage control in electrical power distribution systems has been analyzed and compared, when a nonlinear load is connected across the load bus. The comparison has been made based on the closed-loop frequency resopnse characteristics of the compensated distribution system. A distribution static compensator (DSTATCOM) as a shunt device and a dynamic voltage restorer (DVR) as a series device are considered in the voltage-control mode for the comparison. The power-quality problems which these compensator address include voltage sags/swells, load voltage harmonic distortions, and unbalancing. The effect of various system parameters on the control performance of the compensator can be studied using the proposed analysis. In particular, the performance of the two compensators are compared with the strong ac supply (stiff source) and weak ac-supply (non-still source) distribution system. The experimental verification of the analytical results derived has been obtained using a laboratory model of the single-phase DSTATCOM and DVR. A generalized converter topology using a cascaded multilevel inverter has been proposed for the medium-voltage distribution system. Simulation studies have been performed in the PSCAD/EMTDC software to verify the results in the three-phase system.

Moment-Matched Lognormal Modeling of Uplink Interference with Power Control and Cell Selection

We develop an alternate characterization of the statistical distribution of the inter-cell interference power observed in the uplink of CDMA systems. We show that the lognormal distribution better matches the cumulative distribution and complementary cumulative distribution functions of the uplink interference than the conventionally assumed Gaussian distribution and variants based on it. This is in spite of the fact that many users together contribute to uplink interference, with the number of users and their locations both being random. Our observations hold even in the presence of power control and cell selection, which have hitherto been used to justify the Gaussian distribution approximation. The parameters of the lognormal are obtained by matching moments, for which detailed analytical expressions that incorporate wireless propagation, cellular layout, power control, and cell selection parameters are developed. The moment-matched lognormal model, while not perfect, is an order of magnitude better in modeling the interference power distribution.

Optimized allocation of sectionalizing switches and control and protection devices for reliability indices improvement in distribution systems

Reliability of power supply is related, among other factors, to the control and protection devices allocation in feeders of distribution systems. In this way, optimized allocation of sectionalizing switches and protection devices in strategic points of distribution circuits, improves the quality of power supply and the system reliability indices. In this work, it is presented a mixed integer non-linear programming (MINLP) model, with real and binary variables, for the sectionalizing switches and protection devices allocation problem, in strategic sectors, aimed at improving reliability indices, increasing the utilities billing and fulfilling exigencies of regulatory agencies for the power supply. Optimized allocation of protection devices and switches for restoration, allows that those faulted sectors of the system can be isolated and repaired, re-managing loads of the analyzed feeder into the set of neighbor feeders. Proposed solution technique is a Genetic Algorithm (GA) developed exploiting the physical characteristics of the problem. Results obtained through simulations for a real-life circuit, are presented. © 2004 IEEE.

Power line carrier equipment for relaying, telemetering, load control, remote trip and emergency communication ...

Mode of access: Internet.

Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

Analysis of distrubances in large interconnected power systems

World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.