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Online ISSN 1751-8695 Print ISSN 1751-8687

IET Generation, Transmission & Distribution

Volume 4, Issue 6, June 2010

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Volume 4, Issue 6

June 2010

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    • Harmony search algorithm for transmission network expansion planning
      • Author(s): A. Verma ; B.K. Panigrahi ; P.R. Bijwe
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 663 –673
      • DOI:  10.1049/iet-gtd.2009.0611
      • Type: Article
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      • p. 663 –673 (11)
        Transmission network expansion planning (TNEP) is a very important problem in power systems. It is a mixed integer, non-linear, non-convex optimisation problem, which is very complex and computationally demanding. Various meta-heuristic optimisation techniques have been tried out for this problem. However, scope for even better algorithms still remains. In view of this, a new technique known as harmony search is presented here for TNEP with security constraints. This technique has been reported to be robust and computationally efficient compared to other meta-heuristic algorithms. Results for three sample test systems are obtained and compared with those obtained with genetic algorithm and bacteria-foraging differential evolution algorithm to verify the potential of the proposed algorithm.
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      Solving optimal power flow problems using a probabilistic α-constrained evolutionary approach
      • Author(s): L.M. Honório ; A.M. Leite da Silva ; D.A. Barbosa ; L.F.N. Delboni
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 674 –682
      • DOI:  10.1049/iet-gtd.2009.0208
      • Type: Article
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      • p. 674 –682 (9)
        One of the most difficult tasks in any population-based approach is to deal with large-scale constrained systems without losing computational efficiency. To achieve such goal, a methodology based on two different techniques is presented. First, an evolutionary algorithm based on a cluster-and-gradient-based artificial immune system (CGbAIS) is used to improve computational time. For that, the CGbAIS uses the numerical information provided by the electrical power system and a clustering strategy that eliminates redundant individuals to speed up the convergence process. Second, to increase the capacity of dealing with constraints, a probabilistic α-level of relaxation is used. This approach treats separately the constraints and objective functions. It generates a lexicographic comparison process meaning that, if two individuals have their constraints below the current α-level, the one with the better objective function has a probability of winning the comparison. Otherwise, the individual with the lower penalty is selected regardless the value of the objective function. Combining these concepts together generates a computational framework capable of finding optimal solutions within a very interesting computational time. Applications using a mixed integer and continuous variables will illustrate the performance of the proposed method.
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      Assessment of system voltage sag performance based on the concept of area of severity
      • Author(s): C.-H. Park ; J.-H. Hong ; G. Jang
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 683 –693
      • DOI:  10.1049/iet-gtd.2009.0492
      • Type: Article
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      • p. 683 –693 (11)
        This study presents a new approach for voltage sag assessment based on the concept of ‘area of severity’ (AOS). The network regions, where the fault occurrences will simultaneously lead to voltage sags at different sensitive load points, can be determined by performing an AOS analysis. The impact rankings of the network lines and buses are also addressed. The impact rankings are determined according to the contribution degree of each line and bus faults to the total expected number of voltage sags in the power system. The concepts of AOS and the impact ranking are useful in establishing efficient planning for the mitigation of voltage sags, and for evaluating the relationship between sensitive load points and system voltage sag performance.
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      Scenario reduction for risk-averse electricity trading
      • Author(s): S. Pineda  and  A.J. Conejo
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 694 –705
      • DOI:  10.1049/iet-gtd.2009.0376
      • Type: Article
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      • p. 694 –705 (12)
        Stochastic optimisation models used to identify risk-averse decisions in electricity futures markets are usually hard to solve because of the large number of scenarios representing the uncertain parameters involved. A novel scenario reduction technique is proposed to select those scenarios that, considering the risk aversion of the decision maker, best represent the original scenario set and make the optimisation problem tractable. Two case studies illustrate the performance of the proposed technique to reduce scenarios pertaining to both continuous and discrete uncertain parameters. The advantage of the proposed technique against the existing ones is apparent in highly risk-averse cases.
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      Development of a methodology for clustering electricity-price series to improve customer response initiatives
      • Author(s): A. Gabaldón ; A. Guillamón ; M.C. Ruiz ; S. Valero ; C. Álvarez ; M. Ortiz ; C. Senabre
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 706 –715
      • DOI:  10.1049/iet-gtd.2009.0112
      • Type: Article
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      • p. 706 –715 (10)
        The aim of this study is to propose a methodology in order to obtain a better support management decisions in terms of planning of bids and energy offers in real-time energy markets. Specifically, the authors use self-organising maps and statistical Ward's linkage to classify electricity market prices into different clusters (high homogeneity inside each cluster). In the second stage, the authors use non-parametric estimation to extract some price patterns in the above mentioned clusters. The knowledge contained within these patterns supplies customers with market-based information on which to focus its energy use decisions. The methodology proposed has been applied to New England (USA) market.
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      Extended topological approach for the assessment of structural vulnerability in transmission networks
      • Author(s): E. Bompard ; R. Napoli ; F. Xue
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 716 –724
      • DOI:  10.1049/iet-gtd.2009.0452
      • Type: Article
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      • p. 716 –724 (9)
        Power system vulnerability is a key concern in modern societies and many efforts have been devoted to its analysis. Recently, the wide domain of complex networks that can be used to assess the vulnerability of network systems has been applied to power grids as well with focus on the topological vulnerability of the transmission systems based on its structure in terms of the nodes and their connection patterns. However, a pure topological approach, as proposed in the current literature, fails in capturing the specific features of power systems. The authors propose an extended topological approach, which can incorporate several important features of the power grids such as flow paths, line flow limits and gen/load bus distribution. Also, a set of new metrics able to provide an assessment of the system vulnerability is defined. ‘Net-ability’ measures the aptitude of the grid in transmitting power from generation to load buses efficiently. ‘Path redundancy’ assesses the available redundancy in terms of paths in transmitting power from a generation to a load bus based on entropy. Based on the previous two metrics, the authors introduce a third metric, the ‘survivability’, as a global metric to evaluate the aptitude of the network in assuring the possibility to match generation and demand in case of failures or attacks. The metrics proposed will be applied to different test systems and to a real-transmission system to illustrate their application and effectiveness.
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      Optimal flexible alternative current transmission system device allocation under system fluctuations due to demand and renewable generation
      • Author(s): S.J. Galloway ; I.M. Elders ; G.M. Burt ; B. Sookananta
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 725 –735
      • DOI:  10.1049/iet-gtd.2009.0221
      • Type: Article
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      • p. 725 –735 (11)
        This study proposes two methods for the optimal placement of flexible alternative current transmission system (FACTS) devices considering variations in demand and renewable generation output. The basic optimisation technique utilised is the differential evolution algorithm and the objective is to minimise the cost of generation. The static performance of the FACTS device is considered here. Simulation shows that with renewable generation present in the network, the system state at peak demand is not always the most suitable state to use for the determination of the optimal FACTS allocation. From this, techniques based on the Monte Carlo simulation are proposed to determine the location for which the operation of FACTS device gives highest benefit in terms of saving cost of conventional generation. These techniques collectively are called renewable uncertainty-based optimal FACTS allocation techniques. This study shows the effectiveness of the techniques in the determination of the optimal FACTS placement for networks with a high penetration of renewable generation.
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      Renyi entropy-based classification of daily electrical load patterns
      • Author(s): G. Chicco  and  J. Sumaili Akilimali
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 736 –745
      • DOI:  10.1049/iet-gtd.2009.0161
      • Type: Article
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      • p. 736 –745 (10)
        This study illustrates and discusses an original approach to classify the electricity consumers according to their daily load patterns. This approach exploits the notion of entropy introduced by Renyi for setting up specific clustering procedures. The proposed procedures differ with respect to typical methods adopted for electricity consumer classification, based on the Euclidean distance notion. The algorithms tested include firstly a classical method based on the between-cluster entropy and its slight variation. Then, a novel procedure is presented, based on the calculation of the similarity between centroids, with successive refinement to allow effective identification of the outliers. The outcomes of the classification carried out by using the proposed procedure are compared to the results of other available techniques, using a set of clustering validity indicators for ranking the clustering methods. On the basis of these results, it emerges that the novel procedure exhibits better clustering performance with respect to both the literature approaches and the classical entropy-based method, for different numbers of clusters. The results obtained are of key relevance for assisting the electricity suppliers in identifying a reduced number of load pattern-dependent classes, to be associated with distinct consumer groups for load aggregation or tariff purposes.
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      Online estimation of distorted power system signal parameters
      • Author(s): R. Agha Zadeh ; A. Ghosh ; G. Ledwich ; F. Zare
      • Source: IET Generation, Transmission & Distribution, Volume 4, Issue 6, p. 746 –755
      • DOI:  10.1049/iet-gtd.2009.0090
      • Type: Article
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      • p. 746 –755 (10)
        An algorithm based on the concept of Kalman filtering is proposed in this study for the estimation of power system signal attributes, like amplitude, frequency and phase angle. This technique can be used in protection relays, digital automatic voltage regulators (AVRs), distribution static compensators (DSTATCOMs), flexible AC transmission systems (FACTS) and other power electronics applications. Furthermore, this algorithm is particularly suitable for the integration of distributed generation sources to power grids when fast and accurate detection of small variations of signal attributes are needed. Practical considerations such as the effect of noise, higher order harmonics and computational issues of the algorithm are considered and tested in the study. Several computer simulations are presented to highlight the usefulness of the proposed approach. Simulation results show that the proposed technique can simultaneously estimate the signal attributes, even if it is highly distorted due to the presence of non-linear loads and noise.
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