Optimal power flow solution of integrated AC-DC power system using enhanced differential evolution algorithm

Mustafa

Int Trans Electr Energ Syst

et al. 2019

Summary The ceaseless efforts by power system industries to promote sustainable and competitive electric power market structure in the deregulated environment have given rise to enormous research in the area of transfer capability of transmission networks. Due to high demand for electricity, transmission components are stressed to operate close to their operating limits, and this leads to a decrease in transmission efficiency. To address this issue, efficient evaluation of available transfer capability (ATC) is crucial for system planning, operation, and control. Several approaches have been proposed for ATC computation. Surprisingly, a comprehensive literature review on ATC computation is yet to be efficiently presented. Researchers have been able to come up with fast algorithms, but most of these algorithms are not accurate, and the presented accurate techniques are not fast enough for online applications. This paper presents a comprehensive review of the different approaches for ATC determination. It provides the concepts, methods, and the features of the ATC. For each technique, the state of the art of the several contributions made by researchers has been highlighted. This review reveals that there are issues regarding ATC calculation methods that need attention: the development of fast and accurate algorithm incorporating system dynamics and system uncertainties in ATC determination. Additionally, efforts on the incorporation of renewable energy generation in the ATC evaluation need to be intensified. This review will serve as one in all for researchers as well as a guide for the entrants in this field.

Section: Available Transfer Capability Determination Methodsmentioning

confidence: 99%

Available transfer capability calculation methods: A comprehensive review

Mustafa

Int Trans Electr Energ Syst

et al. 2019

Intl J of Energy Research

“…37,38 , is used to determine the optimum generation schedule without any violation of real time working constraints. The New England-39 bus power network, 39 which consists of 10 generators and 46 transmission lines is selected as the system for validating the proposed work. A very brief summary of previous works in this field is shown in Table .1.…”

Section: Contributionmentioning

confidence: 99%

Impact of optimal power generation scheduling for operating cleaner hybrid power systems with energy storage

Panda

Aviso

Mishra

et al. 2021

De-carbonization of the electric power system, reduction in greenhouse gas emissions and the enhancement of environmental security have emphasized the need for the optimal utilization of renewable/cleaner energy in power system operation. However, unpredictability and intermittency are the major barriers that limit the penetration of renewable power generation (RPG). In this context, large-scale energy storage (LSES) facilities may prove to be an effective means for mitigating the long-term volatility and vulnerability of RPG and subsequently reduce the power dependence on fossil fuel-based generation systems. Thus, the possibility of increasing the penetration of cleaner power may be achieved by simultaneously implementing LSES and an intelligent scheduling strategy so that the hybrid power system may be operated with lower power loss, more cost-effective operation, and an enhanced voltage security.Previous researchers in multiple works have demonstrated the operational analysis and optimization of hybrid configurations with and without storage in stand-alone, islanded and remote operations. In contrast, attempts have been made in this work to incorporate, analyse and validate the impact of LSES facilities (ie, pumped hydroelectric storage (PHS) and compressed air energy storage (CAES)) with benchmark power grid configuration (ie, New-England-39 bus).In this work, a comparative analysis among different hybrid configurations, particularly wind-solar-thermal, wind-solar-hydro-thermal, wind-solarhydro-thermal-PHS and wind-solar-hydro-thermal-CAES is conducted within a multi-objective optimization environment. The proposed design problem is analysed with the inclusion of real-time constrictions in the form of stochastic variation in renewable power output and random disruptions. The modified bacteria foraging algorithm is used to evaluate the optimum generation schedule for which the operational objectives will be achieved for the design problem. Further, using fuzzy membership function, the trade-off between conflicting objectives is portrayed in Pareto optimal domain. Among different hybrid configurations considered, the HPS which incorporates the CAES system exhibits the most superior performance.

Anais Do Congresso Brasileiro De Automática 2020

“…Os coeficientes da função de custo de geração, obtidos de (Sayah & Hamouda, 2019), são apresentados na Tabela 1. a b c 30 0 6,9 0,0193 31 0 3,7 0,0111 32 0 2,8 0,0104 33 0 4,7 0,0088 34 0 2,8 0,0128 35 0 3,7 0,0094 36 0 4,8 0,0099 37 0 3,6 0,0113 38 0 3,7 0,0071 39 0 3,9 0,0064 As simulações foram conduzidas utilizando um computador Intel Core i7 1.80 GHz com 16 GB de RAM e um sistema operacional Windows 10, 64-bits.…”

Section: Descrição Do Sistema E Limitesunclassified

“…Diversas aplicações de FPO nos estudos de planejamento da operação são relatadas na literatura, incluindo sistemas com dispositivos FACTS (Zhang et al, 2012), elos de transmissão em corrente contínua HVDC (Sayah & Hamouda, 2019) e microrredes (Levron et al, 2013). É importante ressaltar que as formulações tradicionais de FPO consideram o sistema em regime permanente, isto é, aspectos dinâmicos das máquinas, cargas e sistemas de controle são desprezados.…”

Section: Introductionunclassified

Minimização do Custo de Geração com Restrição de Estabilidade à Pequenas Perturbações

Amaral

Amarante

Peres

et al. 2020

A otimização de sistemas elétricos de potência operando em regime permanente é realizada em estudos de planejamento da operação através do Fluxo de Potência Ótimo (FPO). O FPO otimiza índices (minimização de custos e perdas, maximização de margem de carregamento, etc.) considerando restrições de tensão, carregamento em circuitos, geração de potência ativa e reativa, entre outros limites. É um problema bem estabelecido na literatura, sendo resolvido por métodos de otimização não lineares. Por outro lado, uma solução fornecida pelo FPO pode ser viável em regime permanente e inviável no regime dinâmico (avaliado em estudos de estabilidade do rotor dos geradores). Um dos estudos de estabilidade realizados é aquele que avalia a habilidade dos geradores síncronos manterem-se em sincronismo após pequenas variações de carga e geração (estabilidade à pequenas perturbações). O mínimo coeficiente de amortecimento do sistema em malha fechada é um índice que pode ser usado para a avaliação desse tipo de estabilidade. Nesse contexto, pode-se incluir uma restrição no FPO que garanta que o coeficiente de amortecimento mínimo seja maior que um valor especificado, dando origem ao SSFPO (Fluxo de Potência Ótimo com Restrição de Small Signal Stability). O SSFPO é um problema não convexo e não linear de difícil solução, ainda não bem estabelecido, e que tem sido tratado na literatura através de métodos de solução baseados em aproximações que podem comprometer a convergência do processo iterativo. Nesse contexto, o presente artigo visa a resolver o SSFPO para minimização do custo de potência ativa gerada através da aplicação da metaheurística baseada em Enxame de Partículas, sem qualquer aproximação para tratamento do índice de estabilidade em regime dinâmico. Estudos para o sistema New England são conduzidos.