Distribution automation is the process by which the collection of data is automated and analyzed, and then controls executed by Utilities. Advanced Distribution Automation (ADA) describe the extension of intelligent control over electrical power grid functions to the distribution level and beyond. It is related to distribution automation that can be enabled via the smart grid. The electrical power grid is typically separated logically into transmission systems and distribution systems. Normally, electric utilities with SCADA systems have extensive control over transmission-level equipment, and increasing control over distribution-level equipment via distribution automation.
Countries around the world have been incorporating automation in their power distribution systems by deploying intelligent devices and smart grid technologies. These developments are expected to improve the scope of the electric power distribution automation systems.
The goal of Advanced Distribution Automation is real-time adjustment to changing loads, generation, and failure conditions of the distribution system, usually without operator intervention. This necessitates control of field devices, which implies enough information technology (IT) development to enable automated decision making in the field and relaying of critical information to the utility control center. The IT infrastructure includes real-time data acquisition and communication with utility databases and other automated systems. Accurate modeling of distribution operations supports optimal decision making at the control center and in the field.
Automated control of devices in distribution systems is closed-loop control of switching devices, voltage controllers, and capacitors based on recommendations of the distribution optimization algorithms.
Distribution System of the Future: The new system concepts will enable ADA functions in the distribution system that contribute to outage prevention and recovery, optimal system performance under changing conditions, and reduced operating costs. Applications which may have greatest potential are operations and efficiency, management of peak loads, predictive technologies and communications for equipment, and system restoration technologies.
Advantages of Advanced Distribution Automation:
- Distributed generation is important in power grids. This generation can help to support local power grids in the presence of blackouts and ease the load on long-distance transmission lines.
- Industrial and residential loads are increasingly controlled through demand response. For example, during periods of peak electrical demand in the summer, the utility control centers may be able to raise the thermostats of houses enrolled in a load reduction program, to temporarily decrease electrical demand from a large number of customers without significantly affecting their comfort.
- To enable demand side management, where homes, businesses, and even electric vehicles may be able to receive real-time pricing signals from their distribution companies and dynamically adjust their own energy consumption profiles to minimize costs.
- To further the penetration and quality of self-healing, which reduces or eliminates outage time through the use of sensor and control systems embedded in the distribution system.
Major components of a DA system:
- Communication systems for distribution automation:As the demands for reliable electric power became greater and as labor became a more significant part of the cost of providing electric power, technologies known as “Supervisory Control and Data Acquisition”, or SCADA for short, were developed which would allow remote monitoring and even control of key system parameters. SCADA systems began to reduce and even eliminate the need for personnel to be on-hand at substations.
- State Estimation: It is well recognized that Distribution System State Estimator (DSSE) is an essential key for implementing smart control strategies such as network restoration, real time system monitoring, energy loss minimization, outage management, security assessment and Volt/Var optimization. Usually these smart distribution network automation functions are implemented through algorithms based on AC power flow model fed by DSSE out put results. To ensure reliability and operational safety, these automation functions must use the rational decision making theory for computing the expected utilities of the consequence of control actions to be applied. To make it possible, it is necessary to quantify the uncertainty related to input information.
In order to deal with this problem, fuzzy state estimation approach and the classical statistical state estimation approach can be put into practice. The input measurements uncertainty are modelled using fuzzy sets theory, and the estimated results are fuzzy numbers that represent all possible states values for a given fuzzy measurement set. A fuzzy estimated state ranges from a minimum to a maximal possible value. The difference between these values is called fuzzy state spread and represents the uncertainty related to the estimated state. Mathematically, the fuzzy state estimation could be modelled as optimization problem aiming to minimize a cost function of the spreads of fuzzy measurements. The algorithm implemented is based on a three-phase power system unbalanced model, considering near real-time measurements from different sources and time scales.
- Fuzzy state estimation approach: A fuzzy number is a generalization of a real number, which does not refer to a single value, but a range of possible values that can be represented by a convex fuzzy set. The fuzzy set theory was developed as an extension of classical set theory (crisp sets). In a classical set theory, the membership of elements in a set is a rigid rule with only two possibilities: belonging or not belonging to the set. On the other hand, in the fuzzy set theory, each element has a degree of membership associated with each set, so that an item can belong to more than one set at same time with distinct degree of membership. Fuzzy numbers has been widely used for modelling vague or inaccurate information, such as linguistic variables like: high, hot, fast, strong etc.
- Classical state estimation approach:The classical statistical state estimation approach is based on the following measurement model:
where z is a mx1 measurement vector, x is a nx1 state vector, ℎ() is a mx1 vector of nonlinear functions that relates the measurements z to the states x, and e is a mx1 error vector. It is assumed that measurement errors are independent.In a general form, the classical state estimation problem is to determine the state vector x that minimizes the following cost function:
In a three-phase approach, the equations ℎ() are basically the active and reactive power flow equations, while the state vector x contains three-phase complex voltages of all electrical buses.The cost function depends on the estimator technique applied. Weighted Least Squares (WLS) and Weighted Least Absolute Value (WLAV) estimators are widely used.
- Feeder reconfiguration for loss reduction:Feeder reconfiguration is defined as altering the topological structures of distribution feeders by changing the open/closed states of the sectionalizing and tie switches. A scheme is presented that utilizes feeder reconfiguration as a planning and/or real-time control tool to restructure the primary feeder for loss reduction.
- Service restoration and load balancing:Service restoration is an emergency control in distribution control centers to restore out-of-service area as soon as possible when a fault occurs in distribution networks. Therefore, it requires fast computation time and high quality solutions for load balancing. A load balance index and heuristic guided best-first search are proposed for these problem. The proposed algorithm consists of two parts. One is to set up a decision tree to represent the various switching operations available. Another is to identify the most effective the set of switches using proposed search technique and a feeder load balance index.
- Volt-var control:Volt-VAR Control or VVC refers to the process of managing voltage levels and reactive power (VAR) throughout the power distribution These two quantities are related, because as reactive power flows over an inductive line that line sees a voltage drop. VVC encompasses devices that purposely inject reactive power into the grid to alter the size of that voltage drop, in addition to equipment that more directly controls voltage.
In the legacy grid, there are three primary tools for carrying out voltage management: Load Tap Changers (LTCs), voltage regulators, and capacitor banks. LTCs and voltage regulators refer to transformers with variable turns ratios that are placed at strategic points in a network and adjusted to raise or lower voltage as is necessary. Capacitor banks manage voltage by “generating” reactive power, and have thus far been the primary tools through which true Volt/VAR control is carried out. These large capacitors are connected to the grid in shunt configuration through switches which, when closed, allow the capacitors to generate VARs and boost voltage at the point of connection.
- Fault location: The measures necessary for determining fault locations can be subdivided into individual steps:
- Fault classification: Insulation and resistance measurement provides information on the fault characteristics. An insulation test measures the insulation resistance between conductor and screen; from the periodic measurement of resistance you can derive the absorption properties of the insulating material.
- Pre-location: Pre-location is used to determine the fault distance. There are predominantly two methods for this:
- Pulse reflection method: A pulse induced at the starting end of the cable reaches the cable fault with a speed of v/2 and then is reflected back toward the starting end of the cable. The elapsed time multiplied by the diffusion speed v/2 gives the distance to the source of the fault.
- Transient method: In the transient method, a breakdown is triggered at the cable fault. This effects a low-resistance short circuit for a few milliseconds. This in turn produces two travelling waves diffusing in opposite directions. These waves are reflected at the cable ends so that they then travel toward each other again in the direction of the cable fault.
- Route tracing and pinpointing: Route tracing is used to determine where the faulty cable lies and pinpointing is the process of determining the exact position of the cable fault.
- Economic analysis/cost benefit analysis:Cost–benefit analysis (CBA) is a systematic approach to estimating the strengths and weaknesses of alternatives in transactions, activities, and functional business requirements. It is used to determine options that provide the best approach to achieve benefits while preserving savings. It may be used to compare potential courses of actions, or to estimate the value against costs of a single decision, project, or policy.
Global Electric Power Distribution Automation Systems (DAS) Market
The global electric power distribution automation systems market size is projected to be worth USD 49.53 billion by 2025. Asia Pacific is projected to be the fastest-growing market and is anticipated to grow at a CAGR of over 6.0% from 2016 to 2025. The rise in the number of manufacturing facilities, coupled with the surging expansion of the industrial sector in Asia Pacific, is expected to fuel the electric power distribution automation systems demand.Furthermore, the growing importance of automation across several end-use industries is anticipated to spur demand in the near future.
The industrial application acquired the largest share of the global electric power distribution automation systems market in 2017. The requirement for efficient electric power distribution automation systems is critically important for the industrial sector, owing to the need for constant power supply and high voltage requirements. Furthermore, need for shorter outage time has supplemented the requirement for various software solutions such as POWER MAP, RAIL SCOPE, RAIL INSPECTOR, which facilitate numerous operations for high-quality power transmission in the industries.