Multi-point Analysis of Economic, Environmental, Static and Dynamic Dispatching of an Energy Mix in the Presence of STATCOM by the U-NSGA-III Genetic Algorithm

Arouna Oloulade,Ramanou Badarou,Amédée Ganye,Adolphe Moukengue Imano,François Xavier Fifatin,Antoine Viannou,Auriole Prudence Omoremy,Mahamoud Tanimomon

doi:10.11648/j.epes.20200905.11

Arouna Oloulade, Ramanou Badarou + Show 6 more

Open Access

https://doi.org/10.11648/j.epes.20200905.11

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Abstract

In an energy environment with multiple production sources, operators are generally confronted with the optimal choice of sources which minimizes polluting gas emissions, losses and marginal production costs while meeting the contractual requirements for maintaining voltage in the ranges required. The present work consisted of optimizing an energy mix in the presence of multi-STATCOM in an interconnected network. Indeed, the (DEE) is a concrete real time problem in electrical energy production systems. This paper shows the impact of STATCOM on static DEE (DEES) and on dynamic DEE (DEED) using the modern genetic algorithm of type U-NSGA-III, which is based on non-dominance sorting. The optimal positioning of two STATCOMs in the application network associated with dynamic dispatching has contributed to the reduction of the total production cost, toxic gas emissions, active losses and then to the improvement of the voltage profiles and the transit of power in the branches. It is observed that the combination of DEED with the optimal positioning of FACTS in an interconnected network constitutes an efficient technico-ecological means to act in the direction of reduction on the triplet consisting of (gas emissions, losses, production cost). The relevance of the results obtained compared to the real case of operating the CEB's interconnected network, justifies the performance of the algorithmic tools developed in the context of this work.

Highlights

The intrinsic characteristics of electrical energy are such that it must be produced, distributed, consumed and accounted at the same time [1]
DEE Algorithm in the Presence of Statcom To solve the problem of DEES or that of DEED, the proposed approach can be represented through the following stages: Step 1: find the ideal position of STATCOMs in the network by multi-objective optimization Step 2: make the network power flow with the STATCOMs positioned at the nodes determined in step 1 Step 3: calculate the coefficients of the matrix B from the results of the power flow obtained in step 3 Step 4: optimize DEE by U-NSGA-III Step 4-1: read the data, namely matrix B, number of generators, generator limits, ramp constraints, power demand per hour, production cost coefficients and emission coefficients
DEED + STATCOM 2.81 145,043.78 1,422.95 00. With regard to this table, we can deduce that the installation of STATCOM followed by the installation of DEED in the interconnected network of the CEB induces an improvement in the performance of this network and makes it possible to satisfy the daily demand for electrical energy at costs reduced and emissions reduced

Summary

Introduction

The intrinsic characteristics of electrical energy are such that it must be produced, distributed, consumed and accounted at the same time [1]. Some authors have worked on optimizing dispatching in the presence of these devices in order to obtain better results This is the case of Suresh et al [10] who integrated the Generalized Unified Power Flow Controller (GUPFC) into the DEE problem with the aim of reducing the total cost of production, active losses and gas emissions. The algorithm they used is the NSUDTPSO (Non-dominated Sorting Uniformly Distributed Two-stage Particle Swarm Optimization).

Statcom Modeling

Cost of production function

Ramp constraints

Results

Conclusion