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The reliability assesment of large power systems, particularly when considering both generation and transmission facilities, is a computationally demanding and complex problem. The sequential Monte Carlo simulation is arguably the most versatile approach for tackling this problem. However, assessing sampled states in the sequential Monte Carlo simulation is time-intensive, rendering its use less appealing, particularly if nonlinear network representation must be deployed. In this context, this paper introduces a tensor-based predictor–corrector approach to reduce the burden of state evaluations in power generation and transmission reliability assessments. The approach allows for searching for sequences of operation points which can be assigned as success states within the sequential Monte Carlo simulation. If required, failure states are evaluated using a cross-entropy optimization algorithm designed to minimize load curtailments taking into account discrete variables. Numerical results emphasize the applicability of the developed algorithms using a small test system and the IEEE-RTS79 test system.

One of the main challenges in smart city models is consumer behaviour, namely guiding the efforts to promote optimal use of energy in the dynamics of the developing cities, through lower energy consumption without impact on the comfort level. This relates to all energy vectors and can be done through different means. The uptake stage of smart metering and information and communication technologies (ICT) varies in different countries, creating the need for tailored innovative approaches in motivating behavioural change. This paper presents the work carried out within the joint research project ITCity (an ICT platform for sustainable energy ecosystem in smart cities) between the European Union and Latin American Countries. Cooperation of energy researchers and experts in ICT and application developers facilitates adoption of a multipurpose interdisciplinary approach. This work aims at providing the smart city and energy research and innovation community broader understanding of factors influencing adoption of energy efficiency technologies. Different ways of guiding optimal energy use are addressed elaborating on the building blocks for a smart city which consider load patterns based on high resolution, high reporting rate measurements, extensive consumer surveys, available communication solution analysis and end-user interaction with the ICT tool based on gamification principles.

This paper evaluates the potential of diverse wind power patterns to balance the global power output of wind farms using the concept of operating reserve assessment. To achieve this, operating reserve assessment models are utilized to evaluate bulk generation systems under several conditions of wind power geographic distribution. Different wind behavior patterns and wind power penetration levels are tested using a modified configuration of the Institute of Electrical and Electronics Engineers Reliability Test System 96 (IEEE RTS-96). The results highlight that on a large country scale system with different wind characteristics, the diversification of wind behavior might be conducive to a compensation of wind power fluctuations, which may significantly decrease the need for system operating reserves. This effect is verified using probability distribution functions of reserve needs estimated by sequential Monte Carlo simulations (SMCS), such that useful information regarding generation capacity flexibility is drawn from the evaluations.

This paper presents an assessment of the forward-backward sweep load flow method to distribution system analysis. The method is formally assessed using fixed-point concepts and the contraction mapping theorem. The existence and uniqueness of the load flow feasible solution is supported by an alternative argument from those obtained in the literature. Also, the closed-form of the convergence rate of the method is deduced and the convergence dependence of loading is assessed. Finally, boundaries for error values per iteration between iterates and feasible solution are obtained. Theoretical results have been tested in several numerical simulations, some of them presented in this paper, thus fostering discussions about applications and future works.

This paper introduces a modified edition of classical Cespedes' load flow method to radial distribution system analysis. In the developed approach, a distribution network is modeled in different complex reference systems and reduced to a set of connected equivalent subnetworks, each without resistance, while graph topology and node voltage solution are preserved. Active power losses are then not dissipated in the modeled subnetworks and active power flows can be obtained as a consequence of radiality. Thus, the proposed method preprocesses a series of variable transformations concomitant to an iterative algorithm using a forward-backward sweep to arrive at the load flow solution. The proposed approach has been tested using literature and actual distribution networks, and efficiency improvements are verified in comparison to Cespedes' load flow method.

This paper evaluates the convergence of a load flow method based on Cespedes' formulation to distribution system steady-state analysis. The method is described and the closed-form of its convergence rate is deduced. Furthermore, convergence dependence of loading and the consequences of choosing particular initial estimates are verified mathematically. All mathematical results have been tested in numerical simulations, some of them presented in the paper.

This paper presents an assessment of the forward-backward sweep load flow method to distribution system analysis. The method is formally assessed using fixed-point concepts and the contraction mapping theorem. The existence and uniqueness of the load flow feasible solution is supported by an alternative argument from those obtained in the literature. Also, the closed-form of the convergence rate of the method is deduced and the convergence dependence of loading is assessed. Finally, boundaries for error values per iteration between iterates and feasible solution are obtained. Theoretical results have been tested in several numerical simulations, some of them presented in this paper, thus fostering discussions about applications and future works.

This paper evaluates the convergence of a load flow method based on Cespedes' formulation to distribution system steady-state analysis. The method is described and the closed-form of its convergence rate is deduced. Furthermore, convergence dependence of loading and the consequences of choosing particular initial estimates are verified mathematically. All mathematical results have been tested in numerical simulations, some of them presented in the paper.

This paper introduces a modified edition of classical Cespedes' load flow method to radial distribution system analysis. In the developed approach, a distribution network is modeled in different complex reference systems and reduced to a set of connected equivalent subnetworks, each without resistance, while graph topology and node voltage solution are preserved. Active power losses are then not dissipated in the modeled subnetworks and active power flows can be obtained as a consequence of radiality. Thus, the proposed method preprocesses a series of variable transformations concomitant to an iterative algorithm using a forward-backward sweep to arrive at the load flow solution. The proposed approach has been tested using literature and actual distribution networks, and efficiency improvements are verified in comparison to Cespedes' load flow method.

This thesis proposes the design and evaluation of a block-oriented agent-based architecture to support the power distribution system operation considering the integration of actively managed distributed energy resources. The architecture was designed in alignment with trends enforced by smart/modern grid concepts, such as promoting decentralized management and control, exploiting distributed energy resources in the operational procedures, modernizing the power distribution systems, and increasing the levels of reliability. Nevertheless, instead of promoting solutions to a future smart/modern grid to be, the proposed architecture was devised to gradually attribute smartness to the system operation using the well-defined notions of intelligence of the agent paradigm. This pragmatical directive allowed creating architectural sets of solutions which attain altogether high levels of flexibility, extensibility, and robustness, permitting the smooth transition from actual to future power distribution systems in a way that improvements in infrastructure are established according to a long-term vision. In the proposed architecture, a block-oriented philosophy of management and control was devised using the agent paradigm to ascribe autonomy to entities responsible to support the operation of particular zones/blocks of the power distribution networks. As consequence, several system capabilities were developed through the application of the agents’ autonomy and interaction, including the support to islanded operation and outage management procedures. The agent-based solutions were designed employing explicit representations of goal-directed behaviors interrelated with agent planning. For this accomplishment, BDI agents were modeled using the JASON agent programming language and interpreter, allowing a high-level representation of the agent’s reasoning through JASON’s syntax. Furthermore, using reference steps of the Prometheus design methodology, the system design is thoroughly described from the abstraction of goals to the coding of agent plans. Once the system design is described, several discussions are provided regarding the transition from the conventional centralized management to the decentralization achieved by the agent-based architecture. At the best of the author’s knowledge, this work marks the first application of JASON and Prometheus to power engineering, thereby highlighting their effectiveness in our research area. Despite the system design matters, it is stated that one of the keys to promote the acceptance of agent-based solutions in the power distribution engineering lies on the development of an environment model, from where the long-term impact of these solutions can be assessed. Therefore, this thesis also proposes the building of a computational environment where the long-term impact of the application of the block-oriented agent-based architecture can be evaluated according to uprisings/downsitting of the power distribution system performance indices. As consequence, it is proposed the concept of an integrated adequacy and security evaluation of power distribution systems with actively managed distributed energy resources, involving power distributed generation units, distributed energy storage devices and controllable loads. Hence, the fundamental concepts behind service adequacy and security were revisited and alternative definitions to these concepts were proposed with focus on the power distribution delivery. Under these definitions, a combined discrete-continuous simulation model capable of providing integrated adequacy and security evaluations is thoroughly described. This simulation model unifies the representation of the long-term failure/repair cycle of system components with aspects of steady-state and dynamic behavior analysis, in a way absent in the state of the art. Furthermore, the simulation model includes several additional developments such as the design of advanced strategies to support load shedding activities, the mathematical disclosure of adverse weather event samplings using a non-homogeneous Poisson process model, the mathematical disclosure of test-functions for the variation of performance indices due to operational/control strategies, and the impact of islanding and islanded operation procedures, droop control schemes, and load shedding strategies on the power distribution system performance indices. All simulation mechanisms were embedded in a computational artifact-based environment modeling whose infrastructure is supported by CArtAgO, a common framework for agent open environments. Hence, at the best of the author’s knowledge, this research also marked the first application of CArtAgO to power engineering modeling and simulation. Therefore, following CArtAgO’s agents and artifacts meta model, an artifact model of a general-purpose power distribution system element was devised. Moreover, an artifact-based scheme was developed to integrate the system state transitions of the simulation model with the solutions provided by the agent interactions. These complex schemes permitted an effective evaluation of the impact of the block-oriented agent-based architecture in the performance of the power distribution systems. In fact, simulation experiments indicated that the active management of distributed energy resources achieved by the architecture may allow significant improvements on the power distribution system performance indices, thereby promoting high levels of service adequacy and security to the utilities’ customers.