Yes / In this paper, a stochastic approach for the operation of active distribution networks within a joint active and reactive distribution market environment is proposed. The method maximizes the social welfare using market based active and reactive optimal power flow (OPF) subject to network constraints with integration of demand response (DR). Scenario-Tree technique is employed to model the uncertainties associated with solar irradiance, wind speed and load demands. It further investigates the impact of solar and wind power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment. A mixed-integer linear programming (MILP) is used to recast the proposed model, which is solvable using efficient off-the shelf branch-and cut solvers. The 16-bus UK generic distribution system is demonstrated in this work to evaluate the effectiveness of the proposed method. Results show that DR integration leads to increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs. / Ministry of Higher Education and Scientific Research of Iraq

Yes / In this paper, a stochastic method is proposed to assess the amount of active and reactive power that can be injected/absorbed to/from grid within a distribution market environment. Also, the impact of wind power penetration on the reactive and active distribution-locational marginal prices is investigated. Market-based active and reactive optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand. The uncertainties are modeled by Scenario-based approach. The proposed model is examined with 16-bus UK generic distribution system. / Supported by the Higher Education Ministry of Iraqi government.

Yes / In this paper, a stochastic method for active distribution networks planning within a distribution market environment considering multi-configuration of wind turbines is proposed. Multi-configuration multi-scenario market-based optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand and different operational status of wind turbines (multiple-wind turbine configurations). Scenario-based approach is used to model the abovementioned uncertainties. The method evaluates the impact of multiple-wind turbine configurations and active network management schemes on the amount of wind power that can be injected into the grid, the distribution locational marginal prices throughout the network and on the social welfare. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. It was shown that multi-wind turbine configurations under active network management schemes, including coordinated voltage control and adaptive power factor control, can increase the amount of wind power that can be injected into the grid; therefore, the distribution locational marginal prices reduce throughout the network significantly.

No / This chapter proposes a novel method for the operation of active distribution networks within a distribution market environment taking into account multi-configuration of wind turbines. Multi-configuration multi-scenario market-based optimal power flow is used to maximise the social welfare considering uncertainties related to wind speed and load demand. Scenario based approach is used to model the uncertainties. The method assesses the impact of multiple-wind turbine configurations on the amount of wind power that can be injected into the grid and the distribution locational marginal prices throughout the network. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Yes / In this paper, a novel deterministic approach for the planning of active distribution networks within a distribution market environment considering multi-configuration of wind turbines (WTs) and photovoltaic (PV) cells is proposed. Multi-configuration multi-period market-based optimal power flow is utilized for maximizing social welfare taking into account uncertainties associated with wind speed, solar irradiance and load demand as well as different operational status of WTs and PVs. Multi-period scenarios method is exploited to model the aforementioned uncertainties. The proposed approach assesses the effect of multiple-configuration of PVs and WTs on the amount of wind and solar power that can be produced, the distribution locational marginal prices all over the network and on the social welfare. The application of the proposed approach is examined on a 30-bus radial distribution network. / This work was supported in part by the Royal Academy of Engineering Distinguished Visiting Fellowship Grant DVF1617/6/45 and by the University of Bradford, UK under the CCIP grant 66052/000000.

Recently, the widespread use of power system controllers, such as PSS and FACTS controllers, has led to the analysis of their effect on the overall stability of power systems. Many studies have been conducted to allocate FACTS controllers so that they achieve optimal power flow conditions in the context of Optimal Power Flow (OPF) analysis. However, these studies usually do not examine the effect of these controllers on the voltage and angle stability of the entire system, considering that the types of these controllers and their control signals, such as reactive power, current, or voltage, have significant effect on the entire system stability. <br /><br /> Due to the recent transition from government controlled to deregulated electricity markets, the relationship between power system controllers and electricity markets has added a new dimension, as the effect of these controllers on the overall power system stability has to be seen from an economic point of view. Studying the effect of adding and tuning these controllers on the pricing of electricity within the context of electricity markets is a significant and novel research area. Specifically, the link among stability, FACTS controllers and electricity pricing should be appropriately studied and modelled. <br /><br /> Consequently, in this thesis, the focus is on proposing and describing of a novel OPF technique which includes a new stability constraint. This technique is compared with respect to existent OPF techniques, demonstrating that it provides an appropriate modelling of system controllers, and thus a better understanding of their effects on system stability and energy pricing. The proposed OPF technique offers a new methodology for pricing the dynamic services provided by the system's controllers. Moreover, the new OPF technique can be used to develop a novel tuning methodology for PSS and FACTS controllers to optimize power dispatch and price levels, as guaranteeing an adequate level of system security. All tests and comparisons are illustrated using 3-bus and 14-bus benchmark systems.

Recently, the widespread use of power system controllers, such as PSS and FACTS controllers, has led to the analysis of their effect on the overall stability of power systems. Many studies have been conducted to allocate FACTS controllers so that they achieve optimal power flow conditions in the context of Optimal Power Flow (OPF) analysis. However, these studies usually do not examine the effect of these controllers on the voltage and angle stability of the entire system, considering that the types of these controllers and their control signals, such as reactive power, current, or voltage, have significant effect on the entire system stability. <br /><br /> Due to the recent transition from government controlled to deregulated electricity markets, the relationship between power system controllers and electricity markets has added a new dimension, as the effect of these controllers on the overall power system stability has to be seen from an economic point of view. Studying the effect of adding and tuning these controllers on the pricing of electricity within the context of electricity markets is a significant and novel research area. Specifically, the link among stability, FACTS controllers and electricity pricing should be appropriately studied and modelled. <br /><br /> Consequently, in this thesis, the focus is on proposing and describing of a novel OPF technique which includes a new stability constraint. This technique is compared with respect to existent OPF techniques, demonstrating that it provides an appropriate modelling of system controllers, and thus a better understanding of their effects on system stability and energy pricing. The proposed OPF technique offers a new methodology for pricing the dynamic services provided by the system's controllers. Moreover, the new OPF technique can be used to develop a novel tuning methodology for PSS and FACTS controllers to optimize power dispatch and price levels, as guaranteeing an adequate level of system security. All tests and comparisons are illustrated using 3-bus and 14-bus benchmark systems.

Yes / This article proposes a novel technique for operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment. The objective of the proposed model is to maximize social welfare using market-based joint active and reactive optimal power flow. First, the intermittent behavior of renewable sources (solar irradiance, wind speed) and load demands is modeled through scenario-tree technique. Then, a network frame is recast using mixed-integer linear programming, which is solvable using efficient off-the-shelf branch-and cut solvers. Additionaly, this article explores the impact of wind and solar power penetration on the active and reactive distribution locational prices within the distribution market environment with integration of ANM schemes and DR. A realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. / This work was supported in part by the Ministry of Higher Education Scientific Research in Iraq and in part by British Academy under Grant GCRFNGR3\1541.

Distributed generators (DGs) are proposed as a possible solution to supply economic and reliable electricity to customers. It is adapted to overcome the challenges that are characterized by centralized generation such as transmission and distribution losses, high cost of fossil fuels and environmental damage. This work presents the basic principles of integrating renewable DGs in low voltage distribution networks and particularly focuses on the operation of DG installations and their impacts on active and reactive power. In this thesis, a novel technique that applies the stochastic approach for the operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment is proposed. The projected model is maximized based on social welfare (SW) using market-based joint active and reactive optimal power flow (OPF). The intermittent behaviour of renewable sources (such as solar irradiance and wind speed) and the load demands are modelled through Scenario-Tree technique. The distributed network frame is recast using mixed-integer linear programming (MILP) that is solved by using the GAMS software and then the obtained results are being analysed and discussed. In addition, the impact of wind and solar power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment is explored in terms of the maximization of SW considering the uncertainty related to solar irradiance, wind speed and load demands. Finally, a realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. Results show that ANM schemes and DR integration lead to an increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs. / Ministry of Higher Education and Scientific Research - Iraq / The selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-02T11:31:43Z No. of bitstreams: 1 Felipe Oliveira.pdf: 3179442 bytes, checksum: 0988804a0a58c2aaf337ea2f5034dc42 (MD5) / Made available in DSpace on 2017-08-02T11:31:43Z (GMT). No. of bitstreams: 1 Felipe Oliveira.pdf: 3179442 bytes, checksum: 0988804a0a58c2aaf337ea2f5034dc42 (MD5) Previous issue date: 2017-02-17 / The locational marginal prices (LMPs) are essential financial guidelines for the electricity industry, which orientates most of the projects and deliberations in electrical market environments. In current scenario of the electricity markets, wind power plants and energy storage systems have been revealing itself as feasible and relevant electrical energy supply alternatives. In this work a generic methodology based on artificial intelligence (AI) techniques is formulated and applied to the calculation and decomposition of LMPs of electric power systems (EPS) with the insertion of energy storage systems and wind farms. In the proposed AI-based methodology the optimal power flow (OPF) model, on which the calculation and decomposition of LMP is based, considers the wind behavior profile volatility, the risks of wind power levels previously scheduled, and the energy storage systems operative peculiarities. The proposed AI-based methodology takes into account the mathematical and computational models of the particle swarm optimization (PSO) algorithm. This proposal was properly implemented and applied for the computation and decomposition of LMPs of test systems and considering different operative scenarios involving conventional power plants, wind farms, and energy storage systems. / Os preços marginais locacionais (LMPs – Locational Marginal Prices) consistem em diretrizes financeiras mercadologicamente indispensáveis para a indústria da eletricidade, os quais norteiam grande parte dos projetos e deliberações no âmbito dos mercados elétricos. No panorama vigente dos mercados elétricos, as plantas de geração eólica e os sistemas de armazenamento de energia vêm progressiva e ininterruptamente se revelando alternativas de suprimento de eletricidade cada vez mais relevantes e viáveis. Neste trabalho, é formulada uma metodologia genérica baseada em técnicas de inteligência artificial (IA) cuja aplicação tem o objetivo de computar e decompor os LMPs associados às barras constituintes de um sistema elétrico de potência (SEP) integrado por geradores convencionais, plantas de geração eólica e por sistemas de armazenamento de energia. Na metodologia IA proposta, o modelo de fluxo de potência ótimo (FPO) sobre o qual se alicerça o cômputo e a decomposição dos LMPs associados às barras de um SEP, leva em consideração a volatilidade inerente ao perfil comportamental dos ventos, os riscos associados à assunção de níveis previamente programados de potência proveniente da geração eólica e as peculiaridades operativas concernentes aos sistemas de armazenamento de energia. Adotando-se os modelos matemáticos e computacionais dos algoritmos de otimização por enxame de partículas (PSO – Particle Swarm Optimization), a metodologia IA proposta foi devidamente implementada e aplicada na aquisição e decomposição dos LMPs associados às barras constituintes de sistemas-testes submetidos a diferentes cenários operativos envolvendo centrais de geração convencionais, plantas de geração eólica e sistemas de armazenamento de energia.