Heuristics for efficient transmission network expansion planning with load uncertainties

This paper proposes an improved harmony search (HS) algorithm for the solution of the static transmission expansion planning (TEP) problem with security constraints. The modification of this method in comparison to the original harmony search algorithm includes the introduction of a variable bandwidth in the memory consideration and the pitch adjustment phase for the selection of the new harmony vector (NHV) in the improvisation step of the algorithm. In that way, if previous harmonies are considered for the NHV, the algorithm allows only the best harmonies of the harmony memory in respect of objective function value to participate in the improvisation of the NHV. The results from the application of the proposed method on IEEE 24-bus reliability test system demonstrate the potentials and the practicality of the proposed HS algorithm. (6 pages)

This paper presents a metaheuristic approach to solve the transmission network expansion planning (TNEP) problem considering non-conventional solution candidates. The TNEP consists on finding the set of new elements required in a power system to meet a given future demand at a minimum cost. The TNEP traditionally considers as candidate solutions the addition of new lines and transformers. The main contribution of this work is the inclusion of non-conventional solution candidates. Such non-conventional solution candidates are namely: repowering of existing circuits and reactive shunt compensation. Also, an AC modeling of the network that allows obtaining more realistic results than the traditional DC model has been considered. The TNEP is represented by means of a non linear mixed integer programming problem which is solved through a hybrid genetic algorithm (HGA). Several tests were performed on two benchmark power systems to show the applicability and effectiveness of the proposed approach.

Harmony search (HS) algorithm is an emerging population oriented stochastic metaheuristic algorithm, which is inspired by the music improvisation process. This paper introduces an Amended harmony search (AHS) algorithm for solving optimization problems. In AHS, an enhanced approach is employed for generating better solution that improves accuracy and convergence speed of harmony search (HS). The effects of various parameters on harmony search algorithm are analyzed in this paper. The proposed approach performs fine tuning of two parameters bandwidth and pitch adjustment rate. The proposed algorithm is demonstrated on complex benchmark functions and results are compared with two recent variants of HS optimization algorithms, improved harmony search (IHS) and highly reliable harmony search (HRHS). Results suggested that the AHS method has strong convergence and has better balance capacity of exploration and exploitation.

An improved harmony search algorithm for power economic load dispatch

The most widely used technique for high-data-rate transmission is orthogonal frequency division multiplexing (OFDM). However, one disadvantage of OFDM systems is that the transmitted signals have a high peak-to-average power ratio (PAPR). High PAPR causes more interference and lower resolution in analogue to digital (A/D) and digital to analogue (D/A) converters. In this paper, Partial Transmit Sequence (PTS) technique using Improved Harmony Search (IHS) algorithm is proposed to solve the high PAPR problem. The PTS technique has a high search complexity because it involves an extensive random search over all possible phase vector combinations, which grows exponentially with the number of phase vectors. IHS improves the accuracy and convergence rate of conventional algorithms while requiring only a few parameters to be adjusted. The modulation method used is Quadrature Phase Shift Keying (QPSK). The performance of PTS and IHS-PTS are analyzed using CCDF graphs with different values of subcarriers and iterations. The PAPR reduction percentage increases more with using IHS-PTS compared to PTS only. To conclude, implementing IHS together with PTS can improve computational complexity in PTS and helps to reduce PAPR values even better in OFDM system.KeywordsImproved Harmony Search (IHS)Orthogonal frequency division multiplexing (OFDM)Peak average power ratio (PAPR)Partial Transmit Sequence (PTS)

The paper is focusing on transmission network expansion planning (TNEP) problem solved using artificial intelligence techniques. It is divided into two parts. The 1st part is dedicated to the particle swarm optimization (PSO) and genetic algorithm (GA) concepts and mechanisms. The mathematical models and the associated software tool are also presented. Practical considerations are discussed. The 2nd part is focusing on case studies. 13 buses test power system, developed by the authors and IEEE 24 RTS have been used. The research work is going to be used in case of the Romanian power system (over 1000 buses).

A novel meta-heuristic model for the multi-year transmission network expansion planning

A reliable approach for solving the transmission network expansion planning problem using genetic algorithms

Inspired by the search method of harmony search algorithms, we propose an other version of improved harmony search(IHS)algorithm to solve integer programming problems. This paper designs a novel improvising strategy which is beneficial to the convergence of algorithm in the early stage of iteration and increasing the diversity of population in the late stage of iteration. Experimental results show that the proposed algorithm can be an efficient alternative for solving integer programming problems.

Impact of wind uncertainty, plug-in-electric vehicles and demand response program on transmission network expansion planning

In electricity transmission networks, energy storage systems (ESS) provide a means of upgrade deferral by smoothing supply and matching demand. We develop a mixed integer programming (MIP) extension to the transmission network expansion planning (TEP) problem that considers the installation and operation of ESS as well as additional circuits. The model is demonstrated on the well known Carver's 6-bus and IEEE 25-bus test circuits for two 24 hour operating scenarios; a short peak, and a long peak. We show optimal location and capacity of storage is sensitive not only to cost, but also variability of demand in the network.

This paper provides a new approach to include the chemotactic behavior of Bacterial Foraging Algorithm (BFOA) in the existing Improved Harmony Search (IHS) algorithm. Extensive computer simulations with CEC-2005 benchmark functions reveal that the proposed algorithm outperforms the existing one with respect to accuracy in determining the optima. The proposed algorithm has successfully been implemented for multi-robot motion planning application. Performance has been studied using the proposed IHS-BFO algorithm and compared with existing IHS and Particle Swarm Optimization (PSO) algorithm.

This work presents the development of multi-objective harmony search (MOHS) algorithm for optimization problem using self-adaptive improved harmony search (SIHS) algorithm which is a variant of recently developed harmony search algorithm (HS) for single objective optimization. The approach used in this work is decomposing of multiple objectives into several single objective functions which are simultaneously optimized in such a way that a nearly uniform distribution of the solutions along the pareto-front is followed. The algorithm upon testing for standard test functions has shown promising results.KeywordsHarmony SearchMulti-objective optimizationPareto front

In this chapter we present a novel method for tracking an arbitrary target through a video sequence using the Harmony Search algorithm called the Harmony Filter. The Harmony Filter models the target using a color histogram and compares potential matches in each video frame using the Bhattacharyya coefficient. Matches are found using the Improved Harmony Search (IHS) algorithm. Experimental results show that the Harmony Filter can robustly track targets in challenging environments while still maintaining real-time performance. We compare the runtime and accuracy performance of the Harmony Filter with other popular methods used in visual tracking including the particle filter and the Kalman Filter. We show that the Harmony filter performs better in both speed and accuracy than similar systems based on the particle filter and the Unscented Kalman Filter (UKF).

The transmission network expansion planning is necessary for supplying the future needs, considering load growth. Furthermore, in restructured environments, transmission lines provide the required infrastructure for creating a competitive environment. In recent years, there has been a significant advancement in storage technologies. This advancement leads to using energy storage systems to postpone the construction or replacement of transmission lines. Therefore, in this paper, the problems of transmission expansion planning and energy storage systems deployment are investigated simultaneously. Considering the presence of storage devices and their effect on network operation cost, in this paper, the operation cost is modeled as an independent objective function along with investment cost. Moreover, the problems of transmission and storage expansion planning are modeled as a tri-objective optimization problem with the objectives of reducing costs and increasing the social welfare index in the power market. The multi-objective shuffled frog leaping evolutionary algorithm is used to solve these problems. The presented model for expansion planning is implemented and analyzed on IEEE 24-bus test system in the presence and absence of energy storage systems, and the effect of change in the price of energy storage systems is studied. The results of this research show that as the technology advances and the storage costs decrease, energy storage systems can play a pivotal role in reducing expansion planning costs of the power network and improving market-based indices in the restructured environment.