Table 2 Algorithm of dynamic proactive control method

From: Early warning and proactive control strategies for power blackouts caused by gas network malfunctions

Inputs

Early warning indicators of impacted gas turbines (\({{{{{\rm{SAE}}}}}}{{{{{{\rm{T}}}}}}}_{i}\), \({{{{{\rm{AL}}}}}}{{{{{{\rm{P}}}}}}}_{0,{i}}\)), parameters and variables of the power system

Parameters

Maximum iteration times (\({{{{{\rm{ite}}}}}}{{{{{{\rm{r}}}}}}}_{\max }\)), control cost tolerance (\({{{{{\rm{tol}}}}}}\)), global control time (\(T\)), time-set ratio (\(\alpha\))

Step 1

Let the iteration number \(k=0\), and the proactive control time \({T}_{i}={{{{{\rm{SAE}}}}}}{{{{{{\rm{T}}}}}}}_{i}\) for each impacted gas turbine \(i\).

Step 2

Solve the linear programming problem (11)-(19) and get the proactive control strategy (\({P}_{{{{{{\rm{d}}}}}},{i},{t}}\), \({P}_{{{{{{\rm{g}}}}}},{i},{t}}\)) with the control cost \({y}_{{{{{{\rm{c}}}}}},k}\).

Step 3

Judge whether the control cost is acceptable or the remaining ALP for each impacted gas turbine is zero, that is, \({y}_{{{{{{\rm{c}}}}}},k}\, < \;{{{{{\rm{tol}}}}}}\) or \({{{{{\rm{AL}}}}}}{{{{{{\rm{P}}}}}}}_{i,{T}_{i}}=0,\,\forall i\in {{{{{{\bf{S}}}}}}}_{{{{{{\rm{IG}}}}}}}\). If yes, go to the output step.

Step 4

Let \({T}_{{{{{{\rm{set}}}}}},i}=\alpha {T}_{i}\) and calculate \({{{{{\rm{AE}}}}}}{{{{{{\rm{T}}}}}}}_{i,{T}_{{{{{{\rm{set}}}}}},i}}\) of each impacted gas turbine.

Step 5

Let \({T}_{i}=\max \left({{{{{\rm{AE}}}}}}{{{{{{\rm{T}}}}}}}_{i}\left({T}_{{{{{{\rm{set}}}}}},i}\right),\,{T}_{i}\right)\).

Step 6

Let \(k=k+1\).

Step 7

Judge whether the iteration number \(k\, < \,{{{{{\rm{ite}}}}}}{{{{{{\rm{r}}}}}}}_{\max }\). If yes, return to step 2.

Outputs

Proactive control strategy (\({P}_{{{{{{\rm{d}}}}}},{i},{t}}\), \({P}_{{{{{{\rm{g}}}}}},{i},{t}}\))

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