DMS Functions Distribution management system

1 dms functions

1.1 network connectivity analysis (nca)
1.2 switching schedule & safety management
1.3 state estimation (se)
1.4 load flow applications (lfa)
1.5 volt-var control (vvc)
1.6 load shedding application (lsa)
1.7 fault management & system restoration (fmsr)
1.8 load balancing via feeder reconfiguration (lbfr)
1.9 distribution load forecasting (dlf)

dms functions

in order support proper decision making , o&m activities, dms solutions should support following functions:

network visualization & support tools
applications analytical & remedial action
utility planning tools
system protection schemes

the various sub functions of same, carried out dms listed below:-

network connectivity analysis (nca)

distribution network covers on large area , catering power different customers @ different voltage levels. locating required sources , loads on larger gis/operator interface difficult. panning & zooming provided normal scada system gui not cover exact operational requirement. network connectivity analysis operator specific functionality helps operator identify or locate preferred network or component easily. nca required analyses , provides display of feed point of various network loads. based on status of switching devices such circuit breaker (cb), ring main unit (rmu) and/or isolators affect topology of network modeled, prevailing network topology determined. nca further assists operator know operating state of distribution network indicating radial mode, loops , parallels in network.

switching schedule & safety management

in territories such uk core function of dms has been support safe switching , work on networks. control engineers prepare switching schedules isolate , make safe section of network before work carried out, , dms validates these schedules using network model. switching schedules can combine telecontrolled , manual (on-site) switching operations. when required section has been made safe, dms allows pemit work (ptw) document issued. after cancellation when work has been finished, switching schedule facilitates restoration of normal running arrangements. switching components can tagged reflect operational restrictions in force.

the network component/connectivity model, , associated diagrams, must kept absolutely date. switching schedule facility therefore allows patches network model applied live version @ appropriate stage(s) of jobs. term patch derived method used maintain wallboard diagrams.

state estimation (se)

the state estimator integral part of overall monitoring , control systems transmission networks. aimed @ providing reliable estimate of system voltages. information state estimator flows control centers , database servers across network. variables of interest indicative of parameters margins operating limits, health of equipment , required operator action. state estimators allow calculation of these variables of interest high confidence despite facts measurements may corrupted noise, or missing or inaccurate.

even though may not able directly observe state, can inferred scan of measurements assumed synchronized. algorithms need allow fact presence of noise might skew measurements. in typical power system, state quasi-static. time constants sufficiently fast system dynamics decay away (with respect measurement frequency). system appears progressing through sequence of static states driven various parameters changes in load profile. inputs of state estimator can given various applications load flow analysis, contingency analysis, , other applications.

load flow applications (lfa)

load flow study important tool involving numerical analysis applied power system. load flow study uses simplified notations single-line diagram , focuses on various forms of ac power rather voltage , current. analyzes power systems in normal steady-state operation. goal of power flow study obtain complete voltage angle , magnitude information each bus in power system specified load , generator real power , voltage conditions. once information known, real , reactive power flow on each branch generator reactive power output can analytically determined.

due nonlinear nature of problem, numerical methods employed obtain solution within acceptable tolerance. load model needs automatically calculate loads match telemeter or forecasted feeder currents. utilises customer type, load profiles , other information distribute load each individual distribution transformer. load-flow or power flow studies important planning future expansion of power systems in determining best operation of existing systems.

volt-var control (vvc)

volt-var control or vvc refers process of managing voltage levels , reactive power (var) throughout power distribution systems. these 2 quantities related, because reactive power flows on inductive line (and lines have inductance) line sees voltage drop. vvc encompasses devices purposely inject reactive power grid alter size of voltage drop, in addition equipment more directly controls voltage.

in legacy grid, there 3 primary tools carrying out voltage management: load tap changers (ltcs), voltage regulators, , capacitor banks. ltcs , voltage regulators refer transformers variable turns ratios placed @ strategic points in network , adjusted raise or lower voltage necessary. capacitor banks manage voltage “generating” reactive power, , have far been primary tools through true volt/var control carried out. these large capacitors connected grid in shunt configuration through switches which, when closed, allow capacitors generate vars , boost voltage @ point of connection. in future, further vvc might carried out smart inverters , other distributed generation resources, can inject reactive power distribution network. vvc application helps operator mitigate dangerously low or high voltage conditions suggesting required action plans vvc equipment. plan give required tap position , capacitor switching state ensure voltage stays close nominal value , optimize volt-var control function utility.

beyond maintaining stable voltage profile, vvc has potential benefits ampacity (current-carrying capacity) of power lines. there loads contain reactive components capacitors , inductors (such electric motors) strain grid. because reactive portion of these loads causes them draw more current otherwise comparable, purely resistive load draw. current can result in heating of equipment transformers, conductors, etc. might need resizing carry total current. ideal power system needs control current flow planning production, absorption , flow of reactive power @ levels in system.

load shedding application (lsa)

electric distribution systems have long stretches of transmission line, multiple injection points , fluctuating consumer demand. these features inherently vulnerable instabilities or unpredicted system conditions may lead critical failure. instability arises power system oscillations due faults, peak deficit or protection failures. distribution load shedding , restoration schemes play vital role in emergency operation , control in utility.

an automated load shedding application detects predetermined trigger conditions in distribution network , performs predefined sets of control actions, such opening or closing non-critical feeders, reconfiguring downstream distribution or sources of injections, or performing tap control @ transformer. when distribution network complex , covers larger area, emergency actions taken downstream may reduce burden on upstream portions of network. in non-automated system, awareness , manual operator intervention play key role in trouble mitigation. if troubles not addressed enough, can cascade exponentially , cause major catastrophic failure.

dms needs provide modular automated load shedding & restoration application automates emergency operation & control requirements utility. application should cover various activities under frequency load shedding (ufls), limit violation , time of day based load shedding schemes performed operator.

fault management & system restoration (fmsr)

reliability , quality of power supply key parameters need ensured utility. reduced outage time duration customer, shall improve on utility reliability indices hence fmsr or automated switching applications plays important role. 2 main features required fmsr are: switching management & suggested switching plan

the dms application receives faults information scada system , processes same identification of faults , on running switching management application; results converted action plans applications. action plan includes switching on/off automatic load break switches / rmus/sectionalizer .the action plan can verified in study mode provided functionality .the switching management can manual/automatic based on configuration.

load balancing via feeder reconfiguration (lbfr)

load balancing via feeder reconfiguration essential application utilities have multiple feeders feeding load congested area. balance loads on network, operator re-routes loads other parts of network. feeder load management (flm) necessary allow manage energy delivery in electric distribution system , identify problem areas. feeder load management monitors vital signs of distribution system , identifies areas of concern distribution operator forewarned , can efficiently focus attention needed. allows more rapid correction of existing problems , enables possibilities problem avoidance, leading both improved reliability , energy delivery performance.

on similar note, feeder reconfiguration used loss minimization. due several network , operational constraints utility network may operated maximum capability without knowing consequences of losses occurring. overall energy losses , revenue losses due these operations shall minimized effective operation. dms application utilizes switching management application this, losses minimization problem solved optimal power flow algorithm , switching plans created similar above function

distribution load forecasting (dlf)

distribution load forecasting (dlf) provides structured interface creating, managing , analyzing load forecasts. accurate models electric power load forecasting essential operation , planning of utility company. dlf helps electric utility make important decisions including decisions on purchasing electric power, load switching, infrastructure development.

load forecasting classified in terms of different planning durations: short-term load forecasting or stlf (up 1 day, medium-term load forecasting or mtlf (1 day 1 year), , long-term load forecasting or ltlf (1–10 years). forecast load precisely throughout year, various external factors including weathers, solar radiation, population, per capita gross domestic product seasons , holidays need considered. example, in winter season, average wind chill factor added explanatory variable in addition used in summer model. in transitional seasons such spring , fall, transformation technique can used. holidays, holiday effect load can deducted normal load estimate actual holiday load better.

various predictive models have been developed load forecasting based on various techniques multiple regression, exponential smoothing, iterative reweighted least-squares, adaptive load forecasting, stochastic time series, fuzzy logic, neural networks , knowledge based expert systems. amongst these, popular stlf stochastic time series models autoregressive (ar) model, autoregressive moving average model (arma), autoregressive integrated moving average (arima) model , other models using fuzzy logic , neural networks.

dlf provides data aggregation , forecasting capabilities configured address today’s requirements , adapt address future requirements , should have capability produce repeatable , accurate forecasts.