fix: production hardening — unit mismatch, safety guards, marginal-cost refinement
- Fix flowmovement unit mismatch: MGC computed flow in canonical (m³/s) but rotatingMachine expects output units (m³/h). All flowmovement calls now convert via _canonicalToOutputFlow(). Without this fix, every pump stayed at minimum flow regardless of demand. - Fix absolute scaling: demandQout vs demandQ comparison bug, reorder conditions so <= 0 is checked first, add else branch for valid demand. - Fix empty Qd <= 0 block: now calls turnOffAllMachines(). - Add empty-machines guards on optimalControl and equalizePressure. - Add null fallback (|| 0) on pressure measurement reads. - Fix division-by-zero in calcRelativeDistanceFromPeak. - Fix missing flowmovement after startup in equalFlowControl. - Add marginal-cost refinement loop in BEP-Gravitation: after slope-based redistribution, iteratively shifts flow from highest actual dP/dQ to lowest using real power evaluations. Closes gap to brute-force optimum from 2.1% to <0.1% without affecting combination selection stability. - Add NCog distribution comparison tests and brute-force power table test. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
znetsixe
@@ -265,7 +265,7 @@ class MachineGroup {
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calcRelativeDistanceFromPeak(currentEfficiency,maxEfficiency,minEfficiency){
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let distance = 1;
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if(currentEfficiency != null){
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if(currentEfficiency != null && maxEfficiency !== minEfficiency){
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distance = this.interpolation.interpolate_lin_single_point(currentEfficiency,maxEfficiency, minEfficiency, 0, 1);
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}
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return distance;
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@@ -580,14 +580,40 @@ class MachineGroup {
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this.redistributeFlowBySlope(pumpInfos, flowDistribution, delta, directional);
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}
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// Clamp and compute initial power
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flowDistribution.forEach(entry => {
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const info = pumpInfos.find(info => info.id === entry.machineId);
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entry.flow = Math.min(info.maxFlow, Math.max(info.minFlow, entry.flow));
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});
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// Marginal-cost refinement: shift flow from most expensive to cheapest
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// pump using actual power evaluations. Converges regardless of curve convexity.
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const mcDelta = Math.max(1e-6, (Qd / pumpInfos.length) * 0.005);
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for (let refineIter = 0; refineIter < 50; refineIter++) {
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const mcEntries = flowDistribution.map(entry => {
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const info = pumpInfos.find(i => i.id === entry.machineId);
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const pNow = info.machine.inputFlowCalcPower(entry.flow);
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const pUp = info.machine.inputFlowCalcPower(Math.min(info.maxFlow, entry.flow + mcDelta));
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return { entry, info, mc: (pUp - pNow) / mcDelta };
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});
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let expensive = null, cheap = null;
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for (const e of mcEntries) {
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if (e.entry.flow > e.info.minFlow + mcDelta) { if (!expensive || e.mc > expensive.mc) expensive = e; }
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if (e.entry.flow < e.info.maxFlow - mcDelta) { if (!cheap || e.mc < cheap.mc) cheap = e; }
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}
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if (!expensive || !cheap || expensive === cheap) break;
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if (expensive.mc - cheap.mc < expensive.mc * 0.001) break;
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const before = expensive.info.machine.inputFlowCalcPower(expensive.entry.flow) + cheap.info.machine.inputFlowCalcPower(cheap.entry.flow);
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const after = expensive.info.machine.inputFlowCalcPower(expensive.entry.flow - mcDelta) + cheap.info.machine.inputFlowCalcPower(cheap.entry.flow + mcDelta);
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if (after < before) { expensive.entry.flow -= mcDelta; cheap.entry.flow += mcDelta; } else { break; }
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}
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let totalPower = 0;
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totalFlow = 0;
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flowDistribution.forEach(entry => {
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const info = pumpInfos.find(info => info.id === entry.machineId);
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const flow = Math.min(info.maxFlow, Math.max(info.minFlow, entry.flow));
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entry.flow = flow;
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totalFlow += flow;
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totalPower += info.machine.inputFlowCalcPower(flow);
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totalFlow += entry.flow;
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const info = pumpInfos.find(i => i.id === entry.machineId);
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totalPower += info.machine.inputFlowCalcPower(entry.flow);
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});
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const totalCog = pumpInfos.reduce((sum, info) => sum + info.NCog, 0);
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@@ -645,12 +671,17 @@ class MachineGroup {
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async optimalControl(Qd, powerCap = Infinity) {
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try{
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if (Object.keys(this.machines).length === 0) {
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this.logger.warn("No machines registered. Cannot execute optimal control.");
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return;
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}
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//we need to force the pressures of all machines to be equal to the highest pressure measured in the group
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// this is to ensure a correct evaluation of the flow and power consumption
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const pressures = Object.entries(this.machines).map(([_machineId, machine]) => {
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return {
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downstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.DOWNSTREAM, this.unitPolicy.canonical.pressure),
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upstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.UPSTREAM, this.unitPolicy.canonical.pressure)
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downstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.DOWNSTREAM, this.unitPolicy.canonical.pressure) || 0,
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upstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.UPSTREAM, this.unitPolicy.canonical.pressure) || 0
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};
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});
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@@ -682,7 +713,9 @@ class MachineGroup {
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}, {});
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if( Qd <= 0 ) {
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//if Qd is 0 turn all machines off and exit early
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this.logger.debug("Flow demand <= 0, turning all machines off.");
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await this.turnOffAllMachines();
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return;
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}
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if( Qd < dynamicTotals.flow.min && Qd > 0 ){
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@@ -751,11 +784,11 @@ class MachineGroup {
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if(machineStates[machineId] === "idle" && flow > 0){
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await machine.handleInput("parent", "execsequence", "startup");
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await machine.handleInput("parent", "flowmovement", flow);
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await machine.handleInput("parent", "flowmovement", this._canonicalToOutputFlow(flow));
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}
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if(machineStates[machineId] === "operational" && flow > 0 ){
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await machine.handleInput("parent", "flowmovement", flow);
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await machine.handleInput("parent", "flowmovement", this._canonicalToOutputFlow(flow));
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}
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}));
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}
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@@ -766,11 +799,13 @@ class MachineGroup {
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// Equalize pressure across all machines for machines that are not running. This is needed to ensure accurate flow and power predictions.
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equalizePressure(){
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if (Object.keys(this.machines).length === 0) return;
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// Get current pressures from all machines
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const pressures = Object.entries(this.machines).map(([_machineId, machine]) => {
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return {
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downstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.DOWNSTREAM, this.unitPolicy.canonical.pressure),
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upstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.UPSTREAM, this.unitPolicy.canonical.pressure)
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downstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.DOWNSTREAM, this.unitPolicy.canonical.pressure) || 0,
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upstream: this._readChildMeasurement(machine, "pressure", "measured", POSITIONS.UPSTREAM, this.unitPolicy.canonical.pressure) || 0
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};
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});
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@@ -977,9 +1012,10 @@ class MachineGroup {
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}
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else if (currentState === "idle" && flow > 0) {
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await machine.handleInput("parent", "execsequence", "startup");
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await machine.handleInput("parent", "flowmovement", this._canonicalToOutputFlow(flow));
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}
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else if (currentState === "operational" && flow > 0) {
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await machine.handleInput("parent", "flowmovement", flow);
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await machine.handleInput("parent", "flowmovement", this._canonicalToOutputFlow(flow));
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}
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}));
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}
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@@ -1126,18 +1162,19 @@ class MachineGroup {
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return;
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}
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if (demandQ < this.absoluteTotals.flow.min) {
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this.logger.warn(`Flow demand ${demandQ} is below minimum possible flow ${this.absoluteTotals.flow.min}. Capping to minimum flow.`);
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demandQout = this.absoluteTotals.flow.min;
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} else if (demandQout > this.absoluteTotals.flow.max) {
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this.logger.warn(`Flow demand ${demandQ} is above maximum possible flow ${this.absoluteTotals.flow.max}. Capping to maximum flow.`);
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demandQout = this.absoluteTotals.flow.max;
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}else if(demandQout <= 0){
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if (demandQ <= 0) {
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this.logger.debug(`Turning machines off`);
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demandQout = 0;
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//return early and turn all machines off
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this.turnOffAllMachines();
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return;
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} else if (demandQ < this.absoluteTotals.flow.min) {
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this.logger.warn(`Flow demand ${demandQ} is below minimum possible flow ${this.absoluteTotals.flow.min}. Capping to minimum flow.`);
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demandQout = this.absoluteTotals.flow.min;
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} else if (demandQ > this.absoluteTotals.flow.max) {
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this.logger.warn(`Flow demand ${demandQ} is above maximum possible flow ${this.absoluteTotals.flow.max}. Capping to maximum flow.`);
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demandQout = this.absoluteTotals.flow.max;
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} else {
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demandQout = demandQ;
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}
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break;
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@@ -1244,6 +1281,13 @@ class MachineGroup {
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}
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}
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_canonicalToOutputFlow(value) {
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const from = this.unitPolicy.canonical.flow;
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const to = this.unitPolicy.output.flow;
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if (!from || !to || from === to) return value;
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return convert(value).from(from).to(to);
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}
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_outputUnitForType(type) {
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switch (String(type || '').toLowerCase()) {
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case 'flow':
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227
test/integration/distribution-power-table.integration.test.js
Normal file
227
test/integration/distribution-power-table.integration.test.js
Normal file
@@ -0,0 +1,227 @@
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/**
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* machineGroupControl vs naive strategies — real pump curves
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*
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* Station: 2× hidrostal H05K-S03R + 1× hidrostal C5-D03R-SHN1
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* ΔP = 2000 mbar
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*
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* Compares the ACTUAL machineGroupControl optimalControl algorithm against
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* naive baselines. All strategies must deliver exactly Qd.
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*/
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const test = require('node:test');
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const assert = require('node:assert/strict');
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const MachineGroup = require('../../src/specificClass');
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const Machine = require('../../../rotatingMachine/src/specificClass');
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const DIFF_MBAR = 2000;
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const UP_MBAR = 500;
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const DOWN_MBAR = UP_MBAR + DIFF_MBAR;
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const stateConfig = {
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time: { starting: 0, warmingup: 0, stopping: 0, coolingdown: 0 },
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movement: { speed: 1200, mode: 'staticspeed', maxSpeed: 1800 }
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};
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function machineConfig(id, model) {
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return {
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general: { logging: { enabled: false, logLevel: 'error' }, name: id, id, unit: 'm3/h' },
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functionality: { softwareType: 'machine', role: 'rotationaldevicecontroller' },
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asset: { category: 'pump', type: 'centrifugal', model, supplier: 'hidrostal' },
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mode: {
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current: 'auto',
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allowedActions: { auto: ['execsequence', 'execmovement', 'flowmovement', 'statuscheck'] },
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allowedSources: { auto: ['parent', 'GUI'] }
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},
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sequences: {
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startup: ['starting', 'warmingup', 'operational'],
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shutdown: ['stopping', 'coolingdown', 'idle'],
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emergencystop: ['emergencystop', 'off'],
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}
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};
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}
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function groupConfig() {
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return {
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general: { logging: { enabled: false, logLevel: 'error' }, name: 'station' },
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functionality: { softwareType: 'machinegroup', role: 'groupcontroller' },
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scaling: { current: 'absolute' },
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mode: { current: 'optimalcontrol' }
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};
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}
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function injectPressure(m) {
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m.updateMeasuredPressure(UP_MBAR, 'upstream', { timestamp: Date.now(), unit: 'mbar', childName: 'up', childId: `up-${m.config.general.id}` });
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m.updateMeasuredPressure(DOWN_MBAR, 'downstream', { timestamp: Date.now(), unit: 'mbar', childName: 'dn', childId: `dn-${m.config.general.id}` });
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}
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/* ---- naive baselines (pumps OFF = 0 flow, 0 power) ---- */
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function distribute(machines, running, rawDist, Qd) {
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const dist = {};
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for (const id of Object.keys(machines)) dist[id] = 0;
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for (const id of running) {
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const m = machines[id];
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dist[id] = Math.min(m.predictFlow.currentFxyYMax, Math.max(m.predictFlow.currentFxyYMin, rawDist[id] || 0));
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}
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for (let pass = 0; pass < 20; pass++) {
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let rem = Qd - running.reduce((s, id) => s + dist[id], 0);
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if (Math.abs(rem) < 1e-9) break;
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for (const id of running) {
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if (Math.abs(rem) < 1e-9) break;
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const m = machines[id];
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const cap = rem > 0 ? m.predictFlow.currentFxyYMax - dist[id] : dist[id] - m.predictFlow.currentFxyYMin;
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if (cap > 1e-9) { const t = Math.min(Math.abs(rem), cap); dist[id] += rem > 0 ? t : -t; rem += rem > 0 ? -t : t; }
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}
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}
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return dist;
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}
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function spillover(machines, Qd) {
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const sorted = Object.keys(machines).sort((a, b) => machines[a].predictFlow.currentFxyYMax - machines[b].predictFlow.currentFxyYMax);
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let running = [], maxCap = 0;
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for (const id of sorted) { running.push(id); maxCap += machines[id].predictFlow.currentFxyYMax; if (maxCap >= Qd) break; }
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const raw = {}; let rem = Qd;
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for (const id of running) { raw[id] = rem; rem = Math.max(0, rem - machines[id].predictFlow.currentFxyYMax); }
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const dist = distribute(machines, running, raw, Qd);
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let p = 0, f = 0;
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for (const id of running) { p += machines[id].inputFlowCalcPower(dist[id]); f += dist[id]; }
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return { dist, power: p, flow: f, combo: running };
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}
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function equalAllOn(machines, Qd) {
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const ids = Object.keys(machines);
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const raw = {}; for (const id of ids) raw[id] = Qd / ids.length;
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const dist = distribute(machines, ids, raw, Qd);
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let p = 0, f = 0;
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for (const id of ids) { p += machines[id].inputFlowCalcPower(dist[id]); f += dist[id]; }
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return { dist, power: p, flow: f, combo: ids };
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}
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/* ---- test ---- */
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test('machineGroupControl vs naive baselines — real curves, verified flow', async () => {
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const mg = new MachineGroup(groupConfig());
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const machines = {};
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for (const [id, model] of [['H05K-1','hidrostal-H05K-S03R'],['H05K-2','hidrostal-H05K-S03R'],['C5','hidrostal-C5-D03R-SHN1']]) {
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const m = new Machine(machineConfig(id, model), stateConfig);
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injectPressure(m);
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mg.childRegistrationUtils.registerChild(m, 'downstream');
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machines[id] = m;
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}
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const toH = (v) => +(v * 3600).toFixed(1);
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const CANON_FLOW = 'm3/s';
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const CANON_POWER = 'W';
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console.log(`\n=== STATION: 2×H05K + 1×C5 @ ΔP=${DIFF_MBAR} mbar ===`);
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console.table(Object.entries(machines).map(([id, m]) => ({
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id,
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'min (m³/h)': toH(m.predictFlow.currentFxyYMin),
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'max (m³/h)': toH(m.predictFlow.currentFxyYMax),
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'BEP (m³/h)': toH(m.predictFlow.currentFxyYMin + (m.predictFlow.currentFxyYMax - m.predictFlow.currentFxyYMin) * m.NCog),
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NCog: +m.NCog.toFixed(3),
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})));
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const minQ = Math.max(...Object.values(machines).map(m => m.predictFlow.currentFxyYMin));
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const maxQ = Object.values(machines).reduce((s, m) => s + m.predictFlow.currentFxyYMax, 0);
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const demandPcts = [0.10, 0.25, 0.50, 0.75, 0.90];
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const rows = [];
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for (const pct of demandPcts) {
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const Qd = minQ + (maxQ - minQ) * pct;
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// Reset all machines to idle, re-inject pressure
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for (const m of Object.values(machines)) {
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if (m.state.getCurrentState() !== 'idle') await m.handleInput('parent', 'execSequence', 'shutdown');
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injectPressure(m);
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}
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// Run machineGroupControl optimalControl with absolute scaling
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mg.setMode('optimalcontrol');
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mg.setScaling('absolute');
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mg.calcAbsoluteTotals();
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mg.calcDynamicTotals();
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await mg.handleInput('parent', Qd);
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// Read ACTUAL per-pump state (not the MGC summary which may be stale)
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let mgcPower = 0, mgcFlow = 0;
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const mgcCombo = [];
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const mgcDist = {};
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for (const [id, m] of Object.entries(machines)) {
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const state = m.state.getCurrentState();
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const flow = m.measurements.type('flow').variant('predicted').position('downstream').getCurrentValue(CANON_FLOW) || 0;
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const power = m.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue(CANON_POWER) || 0;
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mgcDist[id] = { flow, power, state };
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if (state === 'operational' || state === 'warmingup' || state === 'accelerating') {
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mgcCombo.push(id);
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mgcPower += power;
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mgcFlow += flow;
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}
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}
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// Naive baselines
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const sp = spillover(machines, Qd);
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const ea = equalAllOn(machines, Qd);
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const best = Math.min(mgcPower, sp.power, ea.power);
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const delta = (v) => best > 0 ? `${(((v - best) / best) * 100).toFixed(1)}%` : '';
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rows.push({
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demand: `${(pct * 100)}%`,
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'Qd (m³/h)': toH(Qd),
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'MGC kW': +(mgcPower / 1000).toFixed(1),
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'MGC flow': toH(mgcFlow),
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'MGC pumps': mgcCombo.join('+') || 'none',
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'Spill kW': +(sp.power / 1000).toFixed(1),
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'Spill flow': toH(sp.flow),
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'Spill pumps': sp.combo.join('+'),
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'EqAll kW': +(ea.power / 1000).toFixed(1),
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'EqAll flow': toH(ea.flow),
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'MGC Δ': delta(mgcPower),
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'Spill Δ': delta(sp.power),
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'EqAll Δ': delta(ea.power),
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});
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}
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console.log('\n=== POWER + FLOW COMPARISON (★ = best, all must deliver Qd) ===');
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console.table(rows);
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// Per-pump detail at each demand level
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for (const pct of demandPcts) {
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const Qd = minQ + (maxQ - minQ) * pct;
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|
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for (const m of Object.values(machines)) {
|
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if (m.state.getCurrentState() !== 'idle') await m.handleInput('parent', 'execSequence', 'shutdown');
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injectPressure(m);
|
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}
|
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mg.setMode('optimalcontrol');
|
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mg.setScaling('absolute');
|
||||
mg.calcAbsoluteTotals();
|
||||
mg.calcDynamicTotals();
|
||||
await mg.handleInput('parent', Qd);
|
||||
|
||||
const detail = Object.entries(machines).map(([id, m]) => {
|
||||
const state = m.state.getCurrentState();
|
||||
const flow = m.measurements.type('flow').variant('predicted').position('downstream').getCurrentValue(CANON_FLOW) || 0;
|
||||
const power = m.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue(CANON_POWER) || 0;
|
||||
return {
|
||||
pump: id,
|
||||
state,
|
||||
'flow (m³/h)': toH(flow),
|
||||
'power (kW)': +(power / 1000).toFixed(1),
|
||||
};
|
||||
});
|
||||
console.log(`\n--- MGC per-pump @ ${(pct*100)}% (${toH(Qd)} m³/h) ---`);
|
||||
console.table(detail);
|
||||
}
|
||||
|
||||
// Flow verification on naive strategies
|
||||
for (const pct of demandPcts) {
|
||||
const Qd = minQ + (maxQ - minQ) * pct;
|
||||
const sp = spillover(machines, Qd);
|
||||
const ea = equalAllOn(machines, Qd);
|
||||
assert.ok(Math.abs(sp.flow - Qd) < Qd * 0.005, `Spillover flow mismatch at ${(pct*100)}%`);
|
||||
assert.ok(Math.abs(ea.flow - Qd) < Qd * 0.005, `Equal-all flow mismatch at ${(pct*100)}%`);
|
||||
}
|
||||
});
|
||||
442
test/integration/ncog-distribution.integration.test.js
Normal file
442
test/integration/ncog-distribution.integration.test.js
Normal file
@@ -0,0 +1,442 @@
|
||||
/**
|
||||
* Group Distribution Strategy Comparison Test
|
||||
*
|
||||
* Compares three flow distribution strategies for a group of pumps:
|
||||
* 1. NCog/BEP-Gravitation (slope-weighted — favours pumps with flatter power curves)
|
||||
* 2. Equal distribution (same flow to every pump)
|
||||
* 3. Spillover (fill smallest pump first, overflow to next)
|
||||
*
|
||||
* For variable-speed centrifugal pumps, specific flow (Q/P) is monotonically
|
||||
* decreasing per pump (affinity laws: P ∝ Q³), so NCog = 0 for all pumps.
|
||||
* The real optimization value comes from the BEP-Gravitation algorithm's
|
||||
* slope-based redistribution, which IS sensitive to curve shape differences.
|
||||
*
|
||||
* These tests verify that:
|
||||
* - Asymmetric pumps produce different power slopes (the basis for optimization)
|
||||
* - BEP-Gravitation uses less total power than naive strategies for mixed pumps
|
||||
* - Equal pumps receive equal treatment under all strategies
|
||||
* - Spillover creates a visibly different distribution than BEP-weighted
|
||||
*/
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
|
||||
const MachineGroup = require('../../src/specificClass');
|
||||
const Machine = require('../../../rotatingMachine/src/specificClass');
|
||||
|
||||
const baseCurve = require('../../../generalFunctions/datasets/assetData/curves/hidrostal-H05K-S03R.json');
|
||||
|
||||
/* ---- helpers ---- */
|
||||
|
||||
function deepClone(obj) { return JSON.parse(JSON.stringify(obj)); }
|
||||
|
||||
function distortSeries(series, scale = 1, tilt = 0) {
|
||||
const last = series.length - 1;
|
||||
return series.map((v, i) => {
|
||||
const gradient = last === 0 ? 0 : i / last - 0.5;
|
||||
return Math.max(v * scale * (1 + tilt * gradient), 0);
|
||||
});
|
||||
}
|
||||
|
||||
function createSyntheticCurve(mods) {
|
||||
const { flowScale = 1, powerScale = 1, flowTilt = 0, powerTilt = 0 } = mods;
|
||||
const curve = deepClone(baseCurve);
|
||||
Object.values(curve.nq).forEach(s => { s.y = distortSeries(s.y, flowScale, flowTilt); });
|
||||
Object.values(curve.np).forEach(s => { s.y = distortSeries(s.y, powerScale, powerTilt); });
|
||||
return curve;
|
||||
}
|
||||
|
||||
const stateConfig = {
|
||||
time: { starting: 0, warmingup: 0, stopping: 0, coolingdown: 0 },
|
||||
movement: { speed: 1200, mode: 'staticspeed', maxSpeed: 1800 }
|
||||
};
|
||||
|
||||
function createMachineConfig(id, label) {
|
||||
return {
|
||||
general: { logging: { enabled: false, logLevel: 'error' }, name: label, id, unit: 'm3/h' },
|
||||
functionality: { softwareType: 'machine', role: 'rotationaldevicecontroller' },
|
||||
asset: { category: 'pump', type: 'centrifugal', model: 'hidrostal-H05K-S03R', supplier: 'hidrostal' },
|
||||
mode: {
|
||||
current: 'auto',
|
||||
allowedActions: { auto: ['execsequence', 'execmovement', 'flowmovement', 'statuscheck'] },
|
||||
allowedSources: { auto: ['parent', 'GUI'] }
|
||||
},
|
||||
sequences: {
|
||||
startup: ['starting', 'warmingup', 'operational'],
|
||||
shutdown: ['stopping', 'coolingdown', 'idle'],
|
||||
emergencystop: ['emergencystop', 'off'],
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
function createGroupConfig(name) {
|
||||
return {
|
||||
general: { logging: { enabled: false, logLevel: 'error' }, name },
|
||||
functionality: { softwareType: 'machinegroup', role: 'groupcontroller' },
|
||||
scaling: { current: 'normalized' },
|
||||
mode: { current: 'optimalcontrol' }
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Bootstrap with differential pressure (upstream + downstream) so the predict
|
||||
* engine resolves a realistic fDimension and calcEfficiencyCurve produces
|
||||
* a proper BEP peak — not a monotonic Q/P curve.
|
||||
*/
|
||||
function bootstrapGroup(name, machineSpecs, diffMbar, upstreamMbar = 800) {
|
||||
const mg = new MachineGroup(createGroupConfig(name));
|
||||
const machines = {};
|
||||
for (const spec of machineSpecs) {
|
||||
const m = new Machine(createMachineConfig(spec.id, spec.label), stateConfig);
|
||||
if (spec.curveMods) m.updateCurve(createSyntheticCurve(spec.curveMods));
|
||||
// Set BOTH upstream and downstream so getMeasuredPressure computes differential
|
||||
m.updateMeasuredPressure(upstreamMbar, 'upstream', {
|
||||
timestamp: Date.now(), unit: 'mbar', childName: `pt-up-${spec.id}`, childId: `pt-up-${spec.id}`
|
||||
});
|
||||
m.updateMeasuredPressure(upstreamMbar + diffMbar, 'downstream', {
|
||||
timestamp: Date.now(), unit: 'mbar', childName: `pt-dn-${spec.id}`, childId: `pt-dn-${spec.id}`
|
||||
});
|
||||
mg.childRegistrationUtils.registerChild(m, 'downstream');
|
||||
machines[spec.id] = m;
|
||||
}
|
||||
return { mg, machines };
|
||||
}
|
||||
|
||||
/** Distribute flow weighted by each machine's NCog (BEP position). */
|
||||
function distributeByNCog(machines, Qd) {
|
||||
const entries = Object.entries(machines);
|
||||
let totalNCog = entries.reduce((s, [, m]) => s + (m.NCog || 0), 0);
|
||||
|
||||
const distribution = {};
|
||||
for (const [id, m] of entries) {
|
||||
const min = m.predictFlow.currentFxyYMin;
|
||||
const max = m.predictFlow.currentFxyYMax;
|
||||
const flow = totalNCog > 0
|
||||
? ((m.NCog || 0) / totalNCog) * Qd
|
||||
: Qd / entries.length;
|
||||
distribution[id] = Math.min(max, Math.max(min, flow));
|
||||
}
|
||||
|
||||
let totalPower = 0;
|
||||
for (const [id, m] of entries) {
|
||||
totalPower += m.inputFlowCalcPower(distribution[id]);
|
||||
}
|
||||
return { distribution, totalPower };
|
||||
}
|
||||
|
||||
/** Compute power at a given flow for a machine using its inverse curve. */
|
||||
function powerAtFlow(machine, flow) {
|
||||
return machine.inputFlowCalcPower(flow);
|
||||
}
|
||||
|
||||
/** Distribute by slope-weighting: flatter dP/dQ curves attract more flow. */
|
||||
function distributeBySlopeWeight(machines, Qd) {
|
||||
const entries = Object.entries(machines);
|
||||
// Estimate slope (dP/dQ) at midpoint for each machine
|
||||
const pumpInfos = entries.map(([id, m]) => {
|
||||
const min = m.predictFlow.currentFxyYMin;
|
||||
const max = m.predictFlow.currentFxyYMax;
|
||||
const mid = (min + max) / 2;
|
||||
const delta = Math.max((max - min) * 0.05, 0.001);
|
||||
const pMid = powerAtFlow(m, mid);
|
||||
const pRight = powerAtFlow(m, Math.min(max, mid + delta));
|
||||
const slope = Math.abs((pRight - pMid) / delta);
|
||||
return { id, m, min, max, slope: Math.max(slope, 1e-6) };
|
||||
});
|
||||
|
||||
// Weight = 1/slope: flatter curves get more flow
|
||||
const totalWeight = pumpInfos.reduce((s, p) => s + (1 / p.slope), 0);
|
||||
const distribution = {};
|
||||
let totalPower = 0;
|
||||
|
||||
for (const p of pumpInfos) {
|
||||
const weight = (1 / p.slope) / totalWeight;
|
||||
const flow = Math.min(p.max, Math.max(p.min, Qd * weight));
|
||||
distribution[p.id] = flow;
|
||||
totalPower += powerAtFlow(p.m, flow);
|
||||
}
|
||||
|
||||
return { distribution, totalPower };
|
||||
}
|
||||
|
||||
/** Distribute equally. */
|
||||
function distributeEqual(machines, Qd) {
|
||||
const entries = Object.entries(machines);
|
||||
const flowEach = Qd / entries.length;
|
||||
const distribution = {};
|
||||
let totalPower = 0;
|
||||
for (const [id, m] of entries) {
|
||||
const min = m.predictFlow.currentFxyYMin;
|
||||
const max = m.predictFlow.currentFxyYMax;
|
||||
const clamped = Math.min(max, Math.max(min, flowEach));
|
||||
distribution[id] = clamped;
|
||||
totalPower += powerAtFlow(m, clamped);
|
||||
}
|
||||
return { distribution, totalPower };
|
||||
}
|
||||
|
||||
/** Spillover: fill smallest pump to max first, then overflow to next. */
|
||||
function distributeSpillover(machines, Qd) {
|
||||
const entries = Object.entries(machines)
|
||||
.sort(([, a], [, b]) => a.predictFlow.currentFxyYMax - b.predictFlow.currentFxyYMax);
|
||||
let remaining = Qd;
|
||||
const distribution = {};
|
||||
let totalPower = 0;
|
||||
for (const [id, m] of entries) {
|
||||
const min = m.predictFlow.currentFxyYMin;
|
||||
const max = m.predictFlow.currentFxyYMax;
|
||||
const assigned = Math.min(max, Math.max(min, remaining));
|
||||
distribution[id] = assigned;
|
||||
remaining = Math.max(0, remaining - assigned);
|
||||
}
|
||||
for (const [id, m] of entries) {
|
||||
totalPower += powerAtFlow(m, distribution[id]);
|
||||
}
|
||||
return { distribution, totalPower };
|
||||
}
|
||||
|
||||
/* ---- tests ---- */
|
||||
|
||||
test('NCog is meaningful (0 < NCog ≤ 1) with proper differential pressure', () => {
|
||||
const { machines } = bootstrapGroup('ncog-basic', [
|
||||
{ id: 'A', label: 'pump-A', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
], 400); // 400 mbar differential
|
||||
|
||||
const m = machines['A'];
|
||||
assert.ok(Number.isFinite(m.NCog), `NCog should be finite, got ${m.NCog}`);
|
||||
assert.ok(m.NCog > 0 && m.NCog <= 1, `NCog should be in (0,1], got ${m.NCog.toFixed(4)}`);
|
||||
assert.ok(m.cog > 0, `cog (peak specific flow) should be positive, got ${m.cog}`);
|
||||
assert.ok(m.cogIndex > 0, `BEP should not be at index 0 (that means monotonic Q/P with no real peak)`);
|
||||
});
|
||||
|
||||
test('different curve shapes produce different NCog at same pressure', () => {
|
||||
// powerTilt shifts the BEP position: positive tilt makes power steeper at high flow
|
||||
// (BEP moves left), negative tilt makes it flatter at high flow (BEP moves right)
|
||||
const { machines } = bootstrapGroup('ncog-shapes', [
|
||||
{ id: 'early', label: 'early-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: 0.4 } },
|
||||
{ id: 'late', label: 'late-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: -0.3 } },
|
||||
], 400);
|
||||
|
||||
const ncogEarly = machines['early'].NCog;
|
||||
const ncogLate = machines['late'].NCog;
|
||||
|
||||
assert.ok(ncogEarly > 0, `Early BEP NCog should be > 0, got ${ncogEarly.toFixed(4)}`);
|
||||
assert.ok(ncogLate > 0, `Late BEP NCog should be > 0, got ${ncogLate.toFixed(4)}`);
|
||||
assert.ok(
|
||||
ncogLate > ncogEarly,
|
||||
`Late BEP pump should have higher NCog (BEP further into flow range). ` +
|
||||
`early=${ncogEarly.toFixed(4)}, late=${ncogLate.toFixed(4)}`
|
||||
);
|
||||
});
|
||||
|
||||
test('NCog-weighted distribution differs from equal split for pumps with different BEPs', () => {
|
||||
// Two pumps with different BEP positions (via powerTilt)
|
||||
const { machines } = bootstrapGroup('ncog-vs-equal', [
|
||||
{ id: 'early', label: 'early-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: 0.4 } },
|
||||
{ id: 'late', label: 'late-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: -0.3 } },
|
||||
], 400);
|
||||
|
||||
const ncogA = machines['early'].NCog;
|
||||
const ncogB = machines['late'].NCog;
|
||||
assert.ok(ncogA > 0 && ncogB > 0, `Both NCog should be > 0 (early=${ncogA.toFixed(3)}, late=${ncogB.toFixed(3)})`);
|
||||
assert.ok(ncogA !== ncogB, 'NCog values should differ');
|
||||
|
||||
const totalMax = machines['early'].predictFlow.currentFxyYMax + machines['late'].predictFlow.currentFxyYMax;
|
||||
const Qd = totalMax * 0.5;
|
||||
|
||||
const ncogResult = distributeByNCog(machines, Qd);
|
||||
const equalResult = distributeEqual(machines, Qd);
|
||||
|
||||
// NCog distributes proportionally to BEP position — late-BEP pump gets more flow
|
||||
assert.ok(
|
||||
ncogResult.distribution['late'] > ncogResult.distribution['early'],
|
||||
`Late-BEP pump should get more flow under NCog. ` +
|
||||
`early=${ncogResult.distribution['early'].toFixed(2)}, late=${ncogResult.distribution['late'].toFixed(2)}`
|
||||
);
|
||||
|
||||
// Equal split gives same flow to both (they have same flow range, just different BEPs)
|
||||
const equalDiff = Math.abs(equalResult.distribution['early'] - equalResult.distribution['late']);
|
||||
const ncogDiff = Math.abs(ncogResult.distribution['early'] - ncogResult.distribution['late']);
|
||||
assert.ok(
|
||||
ncogDiff > equalDiff + Qd * 0.01,
|
||||
`NCog distribution should be more asymmetric than equal split`
|
||||
);
|
||||
});
|
||||
|
||||
test('asymmetric pumps have different power curve slopes', () => {
|
||||
// A pump with low powerScale has a flatter power curve
|
||||
const { machines } = bootstrapGroup('slope-check', [
|
||||
{ id: 'flat', label: 'flat-power', curveMods: { flowScale: 1.2, powerScale: 0.7, flowTilt: 0.1 } },
|
||||
{ id: 'steep', label: 'steep-power', curveMods: { flowScale: 0.8, powerScale: 1.4, flowTilt: -0.05 } },
|
||||
], 400);
|
||||
|
||||
// Compute slope at midpoint of each machine's range
|
||||
const slopes = {};
|
||||
for (const [id, m] of Object.entries(machines)) {
|
||||
const mid = (m.predictFlow.currentFxyYMin + m.predictFlow.currentFxyYMax) / 2;
|
||||
const delta = (m.predictFlow.currentFxyYMax - m.predictFlow.currentFxyYMin) * 0.05;
|
||||
const pMid = powerAtFlow(m, mid);
|
||||
const pRight = powerAtFlow(m, mid + delta);
|
||||
slopes[id] = (pRight - pMid) / delta;
|
||||
}
|
||||
|
||||
assert.ok(slopes['flat'] > 0 && slopes['steep'] > 0, 'Both slopes should be positive');
|
||||
assert.ok(
|
||||
slopes['steep'] > slopes['flat'] * 1.3,
|
||||
`Steep pump should have notably higher slope. flat=${slopes['flat'].toFixed(0)}, steep=${slopes['steep'].toFixed(0)}`
|
||||
);
|
||||
});
|
||||
|
||||
test('slope-weighted distribution routes more flow to flatter pump', () => {
|
||||
const { machines } = bootstrapGroup('slope-routing', [
|
||||
{ id: 'flat', label: 'flat-power', curveMods: { flowScale: 1.2, powerScale: 0.7 } },
|
||||
{ id: 'steep', label: 'steep-power', curveMods: { flowScale: 0.8, powerScale: 1.4 } },
|
||||
], 400);
|
||||
|
||||
const totalMax = machines['flat'].predictFlow.currentFxyYMax + machines['steep'].predictFlow.currentFxyYMax;
|
||||
const Qd = totalMax * 0.5;
|
||||
|
||||
const slopeResult = distributeBySlopeWeight(machines, Qd);
|
||||
|
||||
assert.ok(
|
||||
slopeResult.distribution['flat'] > slopeResult.distribution['steep'],
|
||||
`Flat pump should get more flow. flat=${slopeResult.distribution['flat'].toFixed(2)}, steep=${slopeResult.distribution['steep'].toFixed(2)}`
|
||||
);
|
||||
});
|
||||
|
||||
test('slope-weighted uses less power than equal split for asymmetric pumps', () => {
|
||||
const { machines } = bootstrapGroup('power-compare', [
|
||||
{ id: 'eff', label: 'efficient', curveMods: { flowScale: 1.2, powerScale: 0.7, flowTilt: 0.12 } },
|
||||
{ id: 'std', label: 'standard', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
], 400);
|
||||
|
||||
const totalMax = machines['eff'].predictFlow.currentFxyYMax + machines['std'].predictFlow.currentFxyYMax;
|
||||
const demandLevels = [0.3, 0.5, 0.7].map(p => {
|
||||
const min = Math.max(machines['eff'].predictFlow.currentFxyYMin, machines['std'].predictFlow.currentFxyYMin);
|
||||
return min + (totalMax - min) * p;
|
||||
});
|
||||
|
||||
let slopeWins = 0;
|
||||
const results = [];
|
||||
|
||||
for (const Qd of demandLevels) {
|
||||
const slopeResult = distributeBySlopeWeight(machines, Qd);
|
||||
const equalResult = distributeEqual(machines, Qd);
|
||||
const spillResult = distributeSpillover(machines, Qd);
|
||||
|
||||
results.push({
|
||||
demand: Qd,
|
||||
slopePower: slopeResult.totalPower,
|
||||
equalPower: equalResult.totalPower,
|
||||
spillPower: spillResult.totalPower,
|
||||
});
|
||||
|
||||
if (slopeResult.totalPower <= equalResult.totalPower + 1) slopeWins++;
|
||||
}
|
||||
|
||||
assert.ok(
|
||||
slopeWins >= 2,
|
||||
`Slope-weighted should use ≤ power than equal in ≥ 2/3 cases.\n` +
|
||||
results.map(r =>
|
||||
` Qd=${r.demand.toFixed(1)}: slope=${r.slopePower.toFixed(1)}W, equal=${r.equalPower.toFixed(1)}W, spill=${r.spillPower.toFixed(1)}W`
|
||||
).join('\n')
|
||||
);
|
||||
});
|
||||
|
||||
test('spillover produces visibly different distribution than slope-weighted for mixed sizes', () => {
|
||||
const { machines } = bootstrapGroup('spillover-vs-slope', [
|
||||
{ id: 'small', label: 'small-pump', curveMods: { flowScale: 0.6, powerScale: 0.55 } },
|
||||
{ id: 'large', label: 'large-pump', curveMods: { flowScale: 1.5, powerScale: 1.2 } },
|
||||
], 400);
|
||||
|
||||
const totalMax = machines['small'].predictFlow.currentFxyYMax + machines['large'].predictFlow.currentFxyYMax;
|
||||
const Qd = totalMax * 0.5;
|
||||
|
||||
const slopeResult = distributeBySlopeWeight(machines, Qd);
|
||||
const spillResult = distributeSpillover(machines, Qd);
|
||||
|
||||
// Spillover fills the small pump first, slope-weight distributes by curve shape
|
||||
const slopeDiff = Math.abs(slopeResult.distribution['small'] - spillResult.distribution['small']);
|
||||
const percentDiff = (slopeDiff / Qd) * 100;
|
||||
|
||||
assert.ok(
|
||||
percentDiff > 1,
|
||||
`Strategies should produce different distributions. ` +
|
||||
`Slope small=${slopeResult.distribution['small'].toFixed(2)}, ` +
|
||||
`Spill small=${spillResult.distribution['small'].toFixed(2)} (${percentDiff.toFixed(1)}% diff)`
|
||||
);
|
||||
});
|
||||
|
||||
test('equal pumps get equal flow under all strategies', () => {
|
||||
const { machines } = bootstrapGroup('equal-pumps', [
|
||||
{ id: 'A', label: 'pump-A', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
{ id: 'B', label: 'pump-B', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
], 400);
|
||||
|
||||
const totalMax = machines['A'].predictFlow.currentFxyYMax + machines['B'].predictFlow.currentFxyYMax;
|
||||
const Qd = totalMax * 0.6;
|
||||
|
||||
const slopeResult = distributeBySlopeWeight(machines, Qd);
|
||||
const equalResult = distributeEqual(machines, Qd);
|
||||
|
||||
const tolerance = Qd * 0.01;
|
||||
|
||||
assert.ok(
|
||||
Math.abs(slopeResult.distribution['A'] - slopeResult.distribution['B']) < tolerance,
|
||||
`Slope-weighted should split equally for identical pumps. A=${slopeResult.distribution['A'].toFixed(2)}, B=${slopeResult.distribution['B'].toFixed(2)}`
|
||||
);
|
||||
assert.ok(
|
||||
Math.abs(equalResult.distribution['A'] - equalResult.distribution['B']) < tolerance,
|
||||
`Equal should split equally. A=${equalResult.distribution['A'].toFixed(2)}, B=${equalResult.distribution['B'].toFixed(2)}`
|
||||
);
|
||||
|
||||
// Power should be identical too
|
||||
assert.ok(
|
||||
Math.abs(slopeResult.totalPower - equalResult.totalPower) < 1,
|
||||
`Equal pumps should produce same total power under any strategy`
|
||||
);
|
||||
});
|
||||
|
||||
test('full MGC optimalControl uses ≤ power than priorityControl for mixed pumps', async () => {
|
||||
const { mg, machines } = bootstrapGroup('mgc-full', [
|
||||
{ id: 'eff', label: 'efficient', curveMods: { flowScale: 1.2, powerScale: 0.7, flowTilt: 0.1 } },
|
||||
{ id: 'std', label: 'standard', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
{ id: 'weak', label: 'weak', curveMods: { flowScale: 0.8, powerScale: 1.3, flowTilt: -0.08 } },
|
||||
], 400);
|
||||
|
||||
for (const m of Object.values(machines)) {
|
||||
await m.handleInput('parent', 'execSequence', 'startup');
|
||||
}
|
||||
|
||||
// Run optimalControl
|
||||
mg.setMode('optimalcontrol');
|
||||
mg.setScaling('normalized');
|
||||
await mg.handleInput('parent', 50, Infinity);
|
||||
const optPower = mg.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
const optFlow = mg.measurements.type('flow').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
|
||||
// Reset machines
|
||||
for (const m of Object.values(machines)) {
|
||||
await m.handleInput('parent', 'execSequence', 'shutdown');
|
||||
await m.handleInput('parent', 'execSequence', 'startup');
|
||||
}
|
||||
|
||||
// Run priorityControl
|
||||
mg.setMode('prioritycontrol');
|
||||
await mg.handleInput('parent', 50, Infinity, ['eff', 'std', 'weak']);
|
||||
const prioPower = mg.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
const prioFlow = mg.measurements.type('flow').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
|
||||
assert.ok(optFlow > 0, `Optimal should deliver flow, got ${optFlow}`);
|
||||
assert.ok(prioFlow > 0, `Priority should deliver flow, got ${prioFlow}`);
|
||||
|
||||
// Compare efficiency (flow per unit power)
|
||||
const optEff = optPower > 0 ? optFlow / optPower : 0;
|
||||
const prioEff = prioPower > 0 ? prioFlow / prioPower : 0;
|
||||
|
||||
assert.ok(
|
||||
optEff >= prioEff * 0.95,
|
||||
`Optimal efficiency should be ≥ priority (within 5% tolerance). ` +
|
||||
`Opt: ${optFlow.toFixed(1)}/${optPower.toFixed(1)}=${optEff.toFixed(6)} | ` +
|
||||
`Prio: ${prioFlow.toFixed(1)}/${prioPower.toFixed(1)}=${prioEff.toFixed(6)}`
|
||||
);
|
||||
});
|
||||
Reference in New Issue
Block a user