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Distflow based state estimation for power distribution networks

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Abstract

A new state estimation method for electrical power distribution systems using the Distflow formulation and the Weighted Least Square method to determine the steady-state operating point is presented. In order to reduce the number of measurements needed for state estimation analysis, a special set of state variables is defined. The proposed methodology is shown to be able to successfully determine the operating conditions of a electrical power distribution system with high automation levels. The proposed approach is tested on the IEEE-37 and IEEE-123 bus test system, reducing the number of state variables up to 60% when compared with conventional state estimation method.

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Abbreviations

\(\varOmega L\) :

Set of system’s lines

\(\varOmega B\) :

Set of system’s nodes

\(\varOmega M\) :

Set of system’s measurements

\({\hat{x}}\) :

State variables of the system

\(J({\hat{x}})\) :

Least squares function

z :

Measurement vector

r :

Vector of measurement residuals

\(h({\hat{x}})\) :

Vector with non-linear functions

W :

Measurement weight matrix

H :

Measurement Jacobian matrix

G :

Gain matrix

v :

Iteration counter

\(Z_{ij}\) :

Impedance of section ij

\(R_{ij}\) :

Resistance of section ij

\(X_{ij}\) :

Reactance of section ij

\(P_{ij}\) :

Active power flow of section ij

\(Q_{ij}\) :

Reactive power flow of section ij

\(P_{ij}^L\) :

Active power loss of section ij

\(Q_{ij}^L\) :

Reactive power loss of section ij

\(V_i^2\) :

Square of the voltage module at node i

\(I_{ij}^2\) :

Square of the current module in section ij

\(P_i^D\) :

Active power demand at node i

\(Q_i^D\) :

Reactive power demand at node i

\(P_i^G\) :

Active power generation at node i

\(Q_i^G\) :

Reactive power generation at node i

\({\overline{Q}}_i^G\) :

Maximum value of reactive power generation at node i

\({\underline{Q}}_i^G\) :

Minimum value of reactive power generation at node i

\(V_0^2\) :

Square of the voltage module at substation node

\(P_0^G\) :

Active power generation at substation node

\(Q_0^G\) :

Reactive power generation at substation node

tol :

Tolerance of the iterative state estimator procedure

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Correspondence to H. A. R. Florez.

Structure of Jacobian matrix H

Structure of Jacobian matrix H

Fig. 2
figure 2

Magnitudes upstream of section ij of an EPDS

In the same way that the backward sweep formulation shown in (12), the power flows \(P_{ij}\) and \(Q_{ij}\) can be calculated as show in Fig. 2:

$$\begin{aligned}&P_{ij}=\sum _{li \in \varOmega L} \left( P_{li} - P_{li}^L \right) - \sum _{ \begin{array}{c} im \in \varOmega L \\ m \ne j \end{array}} P_{im} - P_i^D + P_i^G \end{aligned}$$
(11)
$$\begin{aligned}&Q_{ij}=\sum _{li \in \varOmega L} \left( Q_{li} - Q_{li}^L \right) - \sum _{ \begin{array}{c} im \in \varOmega L \\ m \ne j \end{array}} Q_{im} - Q_i^D + Q_i^G \end{aligned}$$
(12)

where,

$$\begin{aligned}&P_{li}^L = R_{li}\left( \frac{P_{li}^2 + Q_{li}^2}{V_l^2} \right) \end{aligned}$$
(13)
$$\begin{aligned}&Q_{li}^L = X_{li}\left( \frac{P_{li}^2 + Q_{li}^2}{V_l^2} \right) \end{aligned}$$
(14)

Thus, according to the Backward/Forward Distflow formulation, it is possible to obtain the following terms from \(H({\hat{x}})\) directly:

$$\begin{aligned}&\frac{\partial P_{ij}}{\partial P_i^G} = \frac{\partial Q_{ij}}{\partial Q_i^G} = \frac{\partial P_{ij}}{\partial P_j^D} = \frac{\partial Q_{ij}}{\partial Q_j^D} = 1 \end{aligned}$$
(15)
$$\begin{aligned}&\frac{\partial P_{ij}}{\partial P_j^G} = \frac{\partial Q_{ij}}{\partial Q_j^G} = \frac{\partial P_{ij}}{\partial P_i^D} = \frac{\partial Q_{ij}}{\partial Q_i^D} = -1 \end{aligned}$$
(16)
$$\begin{aligned}&\frac{\partial P_{ij}}{\partial Q_i^G} = \frac{\partial Q_{ij}}{\partial P_i^G} = \frac{\partial P_{ij}}{\partial Q_j^G} = \frac{\partial Q_{ij}}{\partial P_j^G} = 0 \end{aligned}$$
(17)
$$\begin{aligned}&\frac{\partial P_{ij}}{\partial Q_i^D} = \frac{\partial Q_{ij}}{\partial P_i^D} = \frac{\partial P_{ij}}{\partial Q_j^D} = \frac{\partial Q_{ij}}{\partial P_j^D} = 0 \end{aligned}$$
(18)

However, due to the lack of equations that relate the magnitudes to the state variables of the system, the chain rule is used to determine the elements of H [17].

1.1 Voltage measurements

The elements of H correspondent to the measured voltage \(V_j^2\) are calculated as shown below.

$$\begin{aligned} \frac{\partial V_j^2}{\partial V_0^2}= & {} \left( \frac{\partial V_j^2}{\partial V_{i}^2}\right) \left( \frac{\partial V_{i}^2}{\partial V_{(i-1)}^2}\right) \cdots \left( \frac{\partial V_{(k+1)}^2}{\partial V_{0}^2}\right) \end{aligned}$$
(19)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_m^G}= & {} \left( \frac{\partial V_j^2}{\partial P_{ij}}\right) \left( \frac{\partial P_{ij}}{\partial P_{(i-1)i}}\right) \cdots \left( \frac{\partial P_{m(m+1)}}{\partial P_{m}^G}\right) \end{aligned}$$
(20)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_m^D}= & {} \left( \frac{\partial V_j^2}{\partial P_{ij}}\right) \left( \frac{\partial P_{ij}}{\partial P_{(i-1)i}}\right) \cdots \left( \frac{\partial P_{m(m+1)}}{\partial P_{m}^D}\right) \end{aligned}$$
(21)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_m^G}= & {} \left( \frac{\partial V_j^2}{\partial Q_{ij}}\right) \left( \frac{\partial Q_{ij}}{\partial Q_{(i-1)i}}\right) \cdots \left( \frac{\partial Q_{m(m+1)}}{\partial Q_{m}^G}\right) \end{aligned}$$
(22)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_m^D}= & {} \left( \frac{\partial V_j^2}{\partial Q_{ij}}\right) \left( \frac{\partial Q_{ij}}{\partial Q_{(i-1)i}}\right) \cdots \left( \frac{\partial Q_{m(m+1)}}{\partial Q_{m}^D}\right) \end{aligned}$$
(23)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_n^G}= & {} \left( \frac{\partial V_j^2}{\partial P_{ij}}\right) \left( \frac{\partial P_{ij}}{\partial P_{j(j+1)}}\right) \cdots \left( \frac{\partial P_{(n-1)n}}{\partial P_{n}^G}\right) \end{aligned}$$
(24)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_n^D}= & {} \left( \frac{\partial V_j^2}{\partial P_{ij}}\right) \left( \frac{\partial P_{ij}}{\partial P_{j(j+1)}}\right) \cdots \left( \frac{\partial P_{(n-1)n}}{\partial P_{n}^D}\right) \end{aligned}$$
(25)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_n^G}= & {} \left( \frac{\partial V_j^2}{\partial Q_{ij}}\right) \left( \frac{\partial Q_{ij}}{\partial Q_{j(j+1)}}\right) \cdots \left( \frac{\partial Q_{(n-1)n}}{\partial Q_{n}^G}\right) \end{aligned}$$
(26)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_n^D}= & {} \left( \frac{\partial V_j^2}{\partial Q_{ij}}\right) \left( \frac{\partial Q_{ij}}{\partial Q_{j(j+1)}}\right) \cdots \left( \frac{\partial Q_{(n-1)n}}{\partial Q_{n}^D}\right) \end{aligned}$$
(27)

Therefore, the high computational effort necessary to evaluate the elements of H for each section of the system is clear. This disadvantage can be mitigated as follows:

*:

Considering that in per unit \(Z_{ij}^2 \ll 1\), \(\forall _{ij} \in \varOmega L\), we have:

$$\begin{aligned} \frac{\partial V_j^2}{\partial V_{i}^2}= & {} 1 + Z_{ij}^2 \left( \frac{P_{ij}^2 + Q_{ij}^2}{V_{i}^4} \right) \approx 1 \end{aligned}$$
(28)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_{ij}}= & {} -2R_{ij} + 2P_{ij}Z_{ij}^2 \approx -2R_{ij} \end{aligned}$$
(29)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_{ij}}= & {} -2X_{ij} + 2Q_{ij}Z_{ij}^2 \approx -2X_{ij} \end{aligned}$$
(30)
*:

Considering that in per unit the terms: \(R_{ij}\frac{P_{ij}}{V_i^2}\ll 1\), \(R_{ij}\frac{P_{ij}}{V_j^2}\ll 1\), \(X_{ij}\frac{Q_{ij}}{V_i^2}\ll 1\) and \(X_{ij}\frac{Q_{ij}}{V_j^2}\ll 1\), \(\forall _{ij} \in \varOmega L\), we have:

$$\begin{aligned} \frac{\partial P_{ij}}{\partial P_{j(j+1)}}= & {} 1 + 2R_{j(j+1)}\left( \frac{P_{j(j+1)}}{V_{j+1}^2}\right) \approx 1 \end{aligned}$$
(31)
$$\begin{aligned} \frac{\partial P_{ij}}{\partial P_{(i-1)i}}= & {} 1 - 2R_{(i-1)i}\left( \frac{P_{(i-1)i}}{V_{i-1}^2}\right) \approx 1 \end{aligned}$$
(32)
$$\begin{aligned} \frac{\partial Q_{ij}}{\partial Q_{j(j+1)}}= & {} 1 + 2X_{j(j+1)}\left( \frac{Q_{j(j+1)}}{V_{j+1}^2}\right) \approx 1 \end{aligned}$$
(33)
$$\begin{aligned} \frac{\partial Q_{ij}}{\partial Q_{(i-1)i}}= & {} 1 - 2X_{(i-1)i}\left( \frac{Q_{(i-1)i}}{V_{i-1}^2}\right) \approx 1 \end{aligned}$$
(34)

Thus, the elements of H shown in (1927) are calculated as follows:

$$\begin{aligned} \frac{\partial V_j^2}{\partial V_0^2}\approx & {} 1 \end{aligned}$$
(35)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_m^G} = - \frac{\partial V_i^2}{\partial P_m^D}\approx & {} 2R_{ij} \end{aligned}$$
(36)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_m^G} = - \frac{\partial V_i^2}{\partial Q_m^D}\approx & {} 2X_{ij} \end{aligned}$$
(37)
$$\begin{aligned} \frac{\partial V_j^2}{\partial P_n^G} = - \frac{\partial V_i^2}{\partial P_n^D}\approx & {} -2R_{ij} \end{aligned}$$
(38)
$$\begin{aligned} \frac{\partial V_j^2}{\partial Q_n^G} = - \frac{\partial V_i^2}{\partial Q_n^D}\approx & {} -2X_{ij} \end{aligned}$$
(39)

1.2 Power flow measurements

Considering that in per unit the terms \(R_{ij}\left( \frac{P_{ij}^2+Q_{ij}^2}{V_i^4}\right) \ll 1\), e \(X_{ij}\left( \frac{P_ij^2+Q_ij^2}{V_i^4}\right) \ll 1\), we have:

$$\begin{aligned} \frac{\partial P_{ij}}{\partial V_0^2} = R_{i(i-1)}\left( \frac{\partial P_{i(i-1)}^2 + Q_{i(i-1)}^2}{\partial V_{(i-1)}^4}\right) \approx 0 \end{aligned}$$
(40)
$$\begin{aligned} \frac{\partial Q_{ij}}{\partial V_0^2} = X_{i(i-1)}\left( \frac{\partial P_{i(i-1)}^2 + Q_{i(i-1)}^2}{\partial V_{(i-1)}^4}\right) \approx 0 \end{aligned}$$
(41)

1.3 Power injection measurements

$$\begin{aligned} \frac{\partial P_i^G}{\partial P_m^G} = \frac{\partial Q_i^G}{\partial Q_m^G} = \frac{\partial P_i^D}{\partial P_m^D} = \frac{\partial Q_i^D}{\partial Q_m^D} = \left\{ \begin{array}{cc} 1, &{} if i=m \\ &{} \\ 0, &{} if i \ne m \end{array}\right. \end{aligned}$$
(42)
$$\begin{aligned} \frac{\partial P_i^G}{\partial Q_m^G} = \frac{\partial P_i^G}{\partial Q_m^D} = \frac{\partial P_i^G}{\partial V_0^2} = \frac{\partial Q_i^G}{\partial P_m^G} = \frac{\partial Q_i^G}{\partial P_m^D} = \frac{\partial Q_i^G}{\partial V_0^2} = 0 \end{aligned}$$
(43)
$$\begin{aligned} \frac{\partial P_i^D}{\partial Q_m^G} = \frac{\partial P_i^D}{\partial Q_m^D} = \frac{\partial P_i^D}{\partial V_0^2} = \frac{\partial Q_i^D}{\partial P_m^G} = \frac{\partial Q_i^D}{\partial P_m^D} = \frac{\partial Q_i^D}{\partial V_0^2} = 0 \end{aligned}$$
(44)

1.4 Current measurements

$$\begin{aligned} \frac{\partial I_{ij}^2}{\partial P_m^G}= & {} -\frac{\partial I_{ij}^2}{\partial P_m^D} \approx \frac{2P_{ij}}{V_j} \end{aligned}$$
(45)
$$\begin{aligned} \frac{\partial I_{ij}^2}{\partial Q_m^G}= & {} -\frac{\partial I_{ij}^2}{\partial Q_m^D} \approx \frac{2Q_{ij}}{V_j} \end{aligned}$$
(46)
$$\begin{aligned} \frac{\partial I_{ij}^2}{\partial P_n^G}= & {} -\frac{\partial I_{ij}^2}{\partial P_n^D} \approx -\frac{2P_{ij}}{V_j} \end{aligned}$$
(47)
$$\begin{aligned} \frac{\partial I_{ij}^2}{\partial Q_n^G}= & {} -\frac{\partial I_{ij}^2}{\partial Q_n^D} \approx -\frac{2Q_{ij}}{V_j} \end{aligned}$$
(48)
$$\begin{aligned} \frac{\partial I_{ij}^2}{\partial V_0^2}\approx & {} \frac{P_{ij}^2+Q_{ij}^2}{V_i^2} \end{aligned}$$
(49)

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Florez, H.A.R., Carreno, E.M., Rider, M.J. et al. Distflow based state estimation for power distribution networks. Energy Syst 9, 1055–1070 (2018). https://doi.org/10.1007/s12667-017-0269-1

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