Network Reconfiguration to Improve Reliability and ... - Coimbra

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List of non-admissible solutions (reveals loads not energized; transformers capacity and heat capacity of all the branches not satisfied; bus voltage limits ...
INESC Coimbra - Jornadas 2009 - Innovative ideas toward the Electrical Grid of the Future -

Network Reconfiguration to Improve Reliability and Efficiency in Distribution Systems 29

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● Romeu M. Vitorino, (Ph.D. Student)

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● Luís P. Neves, (Ph.D.) 56

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● Humberto M. Jorge, (Ph.D.)

Introduction Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

„ Proposal of a new method to improve reliability and also efficiency

(minimization of active power losses) in radial distribution systems through a process of network reconfiguration; „ To evaluate reliability is used the Monte Carlo simulation (MC) and an

historical data of the network (level of reliability and the severity of potential contingencies in each branch); „ Two Perspectives of optimization:

• 1st (no investment) – using only the switches presented in the network; • 2nd (with investment) – possibility to place a limited number of tieswitches (only in certain branches), defined by a decision agent.

Network Reconfiguration to Improve Reliability and Efficiency in Distribution Systems

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Genetic Algorithm Approach (IGA) Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– Main Features of the IGA (Improved Genetic Algorithm) ● List of non-admissible solutions (reveals loads not energized; transformers capacity and heat capacity of all the branches not satisfied; bus voltage limits violation); ● Two-termination criterion (Number of generations and a convergence threshold); ● Adaptive Crossover and Mutation probabilities according to the genetic diversity in the population; ● Suitable coding and decoding technique (obtains a small chromosome length and can assure the radiality of the network); ● Elitist selection (the best individual at the early generation (k) is maintained in the next generation (k+1)). Network Reconfiguration to Improve Reliability and Efficiency in Distribution Systems

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Distribution System Reliability Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– Branch Reliability „ A fundamental element of the network to assure continuity of service.

To define the reliability level of each network branch it was considered the following: Level 1 2 3 4

Failure Very unlikely Unlikely Likely Very likely

Historical information about component failures

„ To better characterize the possible contingencies, were defined

degrees of severity (based on historical data) each with different average interruption durations (“Dav”);

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Distribution System Reliability Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– Monte Carlo Simulation method „ The method considered N trials and, in each trial, an annual number of

contingencies, in locations according to the reliability level of each branch;

„ The interruption duration of each contingency is variable and follows a

normal density curve with a standard deviation (σ) and average (μ). 1 0.9

f ( x; μ , σ ) = e

− ( x − μ )2 2σ

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„ Estimation of the annual reliability indexes in the considered network

configuration. In this study, the total energy not distributed (TEND) is used as the reliability index to minimize.

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Evaluation of the solutions Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– Multi-objective fitness assignment „ A fitness function we want to minimize is used to evaluate the

performance of the solutions and considers two objectives:

fitness = (α1WLoss + α 2TEND ) × 100 „ 1st part – represents the annual active energy loss (WLoss); „ 2nd part – represents the annual total energy not distributed (TEND),

obtained through the MC simulation.

„ Due to the difference between the values of WLoss and TEND it was

used a normalization method (parameters α1 and α2) also capable to reflect the importance of both objectives to the decision agent.

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Case Study – MV network (12.66 kV) Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

Characteristics: Restricted number of branches for tie-switch placement !

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1 substation (8 MVA) 48 transformation units (P =3.8 MW; Q= 2.7 MVAr)

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- Transformation unit ( Public service) - Sectionalizing-Switch - Tie-Switch

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Test Results – 1st Solution Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– 1st perspective: Optimization without investment „

Same weight to efficiency and reliability (w1 = 0.5; w2 = 0.5);

Open Branches WLoss (MWh) TEND (MWh) Fitness value „

Base network

1st Solution

[69-70-71-72-73] 3157.5 4.2924 100

[19-61-69-71-72] 2953.1 4.1801 95.45

Annual Energy Loss reduction (WLoss) of 6.5 % and Total ENergy not Distributed (TEND) reduction of 2.6 %. %

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Test Results – 2nd Solution Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– 2nd perspective: Optimization with investment (1 new tie-switch) „

Same weight to efficiency and reliability (w1 = 0.5; w2 = 0.5);

Open Branches WLoss (MWh) TEND (MWh) Fitness value

Base network

2nd Solution

[69-70-71-72-73] 3157.5 4.2924 100

[15-56-61-69-71] 2613.19 3.0706 77.15

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2nd Solution: WLoss reduction of 17.2 % and TEND reduction of 28.5 %. %

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1st Solution (Without investment and same weight): WLoss reduction of 6.5 % and TEND reduction of 2.6 %.

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Test Results – 3rd Solution Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– 2nd perspective: Optimization with investment (1 new tie-switch) „

Different weight to efficiency and reliability (w1 = 0.3; w2 = 0.7);

Open Branches WLoss (MWh) TEND (MWh) Fitness value

Base network

3rd Solution

[69-70-71-72-73] 3157.5 4.2924 100

[19-45-56-69-73] 2898.69 2.6758 71.17

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3rd Solution (reliability with higher importance): WLoss reduction of 8.2 % and TEND reduction of 37.3 %. %

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2nd Solution (With investment and same weight): WLoss reduction of 17.2 % and TEND reduction of 28.5 %.

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Test Results Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

– Dynamic Adjustment of genetic operator probabilities pc

Gdiv

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Learning of crossover (pc) and mutation (pm) probabilities is dependent on the genetic diversity (Gdiv)

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Maintains the Genetic Diversity

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Prevents premature convergence to local optimum

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Conclusions Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

„ Possibility of obtaining network solutions that allow the simultaneous

optimization of losses and reliability considering different weights; „ Good performance of IGA (convergence speed and stability increased)

due to the introduction of new features (dynamic “pc” and “pm”, …); „ Two-perspective approach was used, giving to the decision agent the

possibility to compare the benefits achieved with both solutions (with and without investment); „ Through network reconfiguration it is possible to make the distribution

system more efficient (in terms of load balancing and voltage stability) considering only the reduction of the electrical losses.

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Perspectives of future developments Jornadas INESCC 2009 - Innovative ideas toward the Electrical Grid of the Future -

„ Inclusion of new objectives in the field of reliability (minimization of

number and duration of the interruptions (NI,DI) according to the geographic zone of each consumer); „ Annual energy loss estimation considering the daily load diagram of

each consumer (LV or MV); „ Consider different network configurations throughout the year (Winter,

Summer and Half-Season); „ Use of Multi-objective optimization techniques (MOO) allowing to

capture multiple solutions of the Pareto front (“Decision Maker” will decide after search).

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