Active Power Loss Index Research Articles

Multi Dimension-Based Optimal Allocation of Uncertain Renewable Distributed Generation Outputs with Seasonal Source-Load Power Uncertainties in Electrical Distribution Network Using Marine Predator Algorithm

In the last few years, the integration of renewable distributed generation (RDG) in the electrical distribution network (EDN) has become a favorable solution that guarantees and keeps a satisfying balance between electrical production and consumption of energy. In this work, various metaheuristic algorithms were implemented to perform the validation of their efficiency in delivering the optimal allocation of both RDGs based on multiple photovoltaic distributed generation (PVDG) and wind turbine distributed generation (WTDG) to the EDN while considering the uncertainties of their electrical energy output as well as the load demand’s variation during all the year’s seasons. The convergence characteristics and the results reveal that the marine predator algorithm was effectively the quickest and best technique to attain the best solutions after a small number of iterations compared to the rest of the utilized algorithms, including particle swarm optimization, the whale optimization algorithm, moth flame optimizer algorithms, and the slime mold algorithm. Meanwhile, as an example, the marine predator algorithm minimized the seasonal active losses down to 56.56% and 56.09% for both applied networks of IEEE 33 and 69-bus, respectively. To reach those results, a multi-objective function (MOF) was developed to simultaneously minimize the technical indices of the total active power loss index (APLI) and reactive power loss index (RPLI), voltage deviation index (VDI), operating time index (OTI), and coordination time interval index (CTII) of overcurrent relay in the test system EDNs, in order to approach the practical case, in which there are too many parameters to be optimized, considering different constraints, during the uncertain time and variable data of load and energy production.

Optimal allocation of renewable distributed generators and shunt capacitors in distribution system using hybrid intelligent approach

Increased utilisation of naturally available energy sources in a distribution system (DS) is customary in recent years. These RES are intermittent in nature and impact the system performance significantly. In this paper, a methodology is utilised for bidding the lowest price to the consumer based on the availability of RES. A physical communication infrastructure between the utility and user is enabled to coordinate between the RES dominant utility and consumers. The main objectives of this communication enabled user utility interface system are to minimise power loss and enhance the voltage profile simultaneously. A multi-objective approach considering active power loss index (ALPI), voltage deviation index (VDI), and voltage stability index (VSI) are presented to solve the renewable distributed generation (RDG) and shunt capacitors (SCs) allocation problem. A combination of sensitivity analysis and random walk moth flame optimisation (RWMFO) is utilised for solving the aforementioned multi-objective function. IEEE 33 and 69 bus test systems are taken for analysis. Finally, the implemented method is compared with recent techniques available in the literature.

Enhanced Sine–Cosine Algorithm for Optimal Planning of Distribution Network by Incorporating Network Reconfiguration and Distributed Generation

One of the important directions of the current research trend in distribution network planning in the prevailing smart grid scenario, is to explore various possibilities to enhance the performance of these networks without expanding the existing infrastructure. This paper proposes an enhanced sine–cosine algorithm (ESCA) to obtain an optimally planned system by simultaneous incorporation of network reconfiguration (NR) and DG allocation. In the proposed algorithm, the SCA is enhanced with neighborhood search strategy and self-adapting levy mutation strategy to ensure proper balance between exploration and exploitation during different reconfiguration phases. A multi-objective function is formulated considering the reduction of total real power loss and annual operation costs with suitable weights without violating the system operating constraints. The proposed algorithm is successfully experimented on 33- and 69-bus distribution system with four distinct scenarios of NR and DG allocation, and its performance assessment is based on technical (total system active power loss index, overall voltage stability index and voltage profile improvement index), economic (total system operation cost index) and reliability (expected energy not supplied index) indices. As the computation of reliability index adds complexity to the problem, a graph theory-based algorithm is proposed for its accurate calculation. The obtained results showed the effectiveness of ESCA for solving simultaneous NR and DG allocation problem over other competitive algorithms, and its robustness is confirmed through a detailed statistical analysis such as plotting of box plots, normality checking and two nonparametric tests, namely Friedman ANOVA and Wilcoxon signed rank tests.

Optimal Distributed Generation Placement with Multiple Objectives Considering Probabilistic Load

In this paper, optimal DG sizing and siting has been obtained considering three objectives i.e. active power loss index (APLI), line loading index (LLI) and voltage deviation index (VDI). Multiple objective NSGA-II method along with fuzzy satisfying method (FSM) has been used to solve multiple objective optimization problem. Probabilistic load model has been considered in this study. A two point estimate (2PEM) method has been used carry out o obtain probabilistic load flow solution. The analysis has been carried out for IEEE 33 radial bus test system. The analysis has been carried out using coding in MATLAB.

Placement of DG and Capacitor for Loss Reduction, Reliability and Voltage Improvement in Distribution Networks Using BPSO

This paper presents multi-objective function for optimally determining the size and location of distributed generation (DG) and capacitor in distribution systems for power loss minimization, reliability and voltage improvement. The objective function proposed in this paper includes reliability index, active power loss index, DG's and capacitor's investment cost index and voltage profile index which is minimized using binary particle swarm optimization algorithm (BPSO). The effectiveness of the proposed method is examined in the 10 and 33 bus test systems and comparative studies are conducted before and after DG and capacitor installation in the test systems. Results illustrate significant losses reduction and voltage profile and reliability improvement with presence of DG unit and capacitor.

Sensitivity analysis applied to nodal technical losses evaluation in power transmission systems

SUMMARY Sensitivity analysis oriented by optimal power flow problem is applied in this work to estimate nodal technical losses in power transmission networks in a smart grid environment. This approach aims to efficiently provide active power loss indices as a result of load variations at each single load bus connected to the system. Unlike the power flow algorithm, this technique does not require an iterative process to find the solution, which results in a faster methodology with high accuracy and reduced computational cost, even when considering all the characteristics of the system. The methodology starts from a known optimal solution obtained by optimal power flow, considered as the base case. From the base case solution, new solutions can be evaluated by sensitivity analysis when system load bus perturbations occur. Tests were carried out on the IEEE 14 and 118 bus systems in order to evaluate the proposed technique performance. Copyright © 2012 John Wiley & Sons, Ltd.