Abstract The benefits of complementarity between renewable energy sources have been presented as having a positive impact, but it has been neglected in generation expansion planning studies. In this paper the complementarity between renewable energy sources and regions of Brazil is characterized and the correlation coefficients are analyzed. A methodology is also proposed to optimize the complementarity between the sources, reducing the energy storage requirements. The methodology is applied to the Brazilian case to meet the projected demand for 2050 with a 100% renewable system and the complementarity is analyzed. The characterization of the data allowed us to propose five solar regions, four wind regions, three hydro regions and a region to represent the biomass. It was possible to find complementarity (negative correlation) of: 0.97 between hydro regions; 0.86 between wind and hydro regions and; 0.96 between biomass and hydro. The proposed methodology allowed us to know which regions and their respective technologies best benefit the electrical system, being the North for solar and the Northeast for wind. Finally, it was possible to reduce the demand for water storage with sources and regions that complement the seasonal hydro drought period.

Abstract The insertion of new distributed energy resources, such as distributed generation (DG), energy storage systems (ESS), demand response (DR), and microgrids (MG), is emerging, bringing new challenges to the current distribution network. In this regard, the active distribution networks (I) with multi-microgrids concept appears. The present paper proposes a hierarchical (master-slave problem) computational model to achieve optimal coordinated operation of multi-microgrids connected to an I. Day-ahead operation planning of an I was formulated as a multiperiod non-linear optimal power flow model, resulting in a non-linear optimization problem, additionally, the day-ahead operation planning of MGs was formulated as a multiperiod linearized optimal power flow resulting in a mixed-integer linear optimization problem. Numerical results on four different test-system microgrids connected to a 359-nodes ADNs test-system belonging to a Brazilian distribution company show the effectiveness of the proposed model and solution strategy. Three cases have been tested: with a maximum load-shedding restriction, without this restriction, and considering insertion of DG. Besides, the hierarchical model can evaluate how much losses and load shedding take effect without integrated operation and expansion planning of emerging distributed networks. This study showed the importance of analyzing the systemic impact of integrating multi-MGs and I synergistic operation interactions, resulting in improvements in the voltage quality levels, operation costs, and power losses. The results showed that, including DG in the system, the costs were reduced by 13,48% compared to the case base.

Abstract Increasing global temperatures over the past years have become a worry. To mitigate this, countries have set out to decrease their greenhouse gas emissions soon. A major contributor to these emissions has been the transport sector. Electric mobility has appeared as an opportunity to decarbonize this sector. With this in mind, Fernando de Noronha Island, a UNESCO World Heritage Site, has determined to ban all fossil fuel vehicles by 2030. Understanding the impact electric vehicles can have on the island's distribution grid is fundamental to achieving this goal. To determine these impacts, electrical vehicle chargers were added to the model of the island's power system in GridLad-D. Apart from these chargers, the impact of adding an extra carport charger fitted with solar panels was also determined. In total, six different charging scenarios were simulated, with each varying the period in which vehicle charging was allowed to take place. The impacts were determined for the day, afternoon, and night charging, with and without the presence of a carport. The parameters measured include system power demand, voltage, and total losses. From the results, it was possible to determine the charging strategy that causes the least and most impact on the system’s distribution grid.

Abstract: Microgrids (MD) is a new technology to improve efficiency, resilience, and reliability in the electricity sector. MD are most likely to have a clean energy generation, but the increase of microgrids with this kind of generation brings new challenges for energy management (EMS), especially concerning load uncertainties and variation of energy generation. In this context, this study has the main objective to propose a method of how to attend this matter, verifying the difference between the day before and real-time. The EMS proposed analyses the MD in real-time, calculating the deviation between dispatched and what was predicted to happen in the operation point in a three-dimensional analysis approach, considering renewable energy generation, battery State of Charge (SOC) and load curve. The system categorized the deviation in three possible quantities (small, medium, or high) and it acts accordingly. For the Next Operation Point predictor are used an artificial neural network (ANN) methodology. For the Decision Support System, it’s used a fuzzy logic system to adjust the next operation point, and it uses a mixed-integer linear programming (MILP) approach when the deviation is too high, and the dispatched operation is unfeasible. Simulations with real data and information of a pilot project of MD are carried out to test and validate the proposed method. Results show that the methodology used to attend the matters of uncertainties and variation of energy generation. A reduction of operational cost is observed in the simulations.

Abstract Distribution power grids are continuously changing, mainly due to the insertion of distributed energy resources. Since the late 90's the distribution generation insertion has been growing, changing the planning and operation of the conventional grid. More recently, storage systems are also being placed on the distribution power system, aiming to improve system power quality and reliability. In this context of active grids, an Optimum Power Flow (OPF) was proposed, integrating generation from distributed generation with photovoltaic systems as well as a battery energy storage, which could be located at different feeder busses, including the substation bus. The OPF was modeled in a multiperiod structure, allowing simultaneous evaluation of all steps within the time horizon, being solved with the interior points method implemented in python. Different scenarios were evaluated considering different distributed generation levels, as well as battery placement at the substation bus and in the middle of the grid. From the multiperiod OPF results, it is obtained the minimization of losses and operational costs of the system, besides the minimum battery cost and the optimum behavior of charge and discharge of the battery.

Abstract Microgrids (MGs) have increasingly attracted the attention of researchers, government officials, and electricity companies for the values and services they can add to the grid. They can operate independently as a single controllable unit in a coordinated way while connected or islanded, which make them suitable to integrate the growing amount of distributed energy resources (DERs) into the distribution network (DN). An active distribution network with high penetration of DERs could be redefined into a collection of microgrids in different layers, pooling their resources together to enhance the grid’s performance in the sense of electricity as a service. However, enabling a microgrid-based power system infrastructure poses challenges concerning operation and control. In this paper, a comprehensive overview of research topics regarding microgrid operation are shown in a hierarchical or stratified manner, looking for a holistic vision of a microgrid-based distribution system. First, multi-objective optimization within one microgrid is formulated aiming to minimize costs and maximize battery life is presented. Second, the interaction among MGs, DERs and the DN was modeled using the OPF technique to represent the operation of the grid as a whole. Following, a methodology for collaborative optimization of multiple MGs operating together is presented and at last a theoretical framework for MG operation through decentralized energy markets is discussed. As a result, this paper aims to contribute to a broad vision of the distribution system based on microgrid operation in all its levels.

ABSTRACT The present article focuses on the construction of an Intelligent System for the Project Start-Stop Logic of Hydropower Plants, work carried out as master dissertation, allowing the retention of knowledge of previous cases which set a valuable intellectual capital, organizing knowledge generated by specialists and consultants of the area. The tool aims at saving time as well as standardizing solutions, allowing future developments for the construction of other necessary logic (such as those related to asset management and tools to aid the operation and maintenance of hydroelectric power plants). The MyCBR, software that proved to be of easy programming, but with some limitations, is used for such an attempt of a shell of current use. The recovery of the cases based on calculations of global and local similarity allows the selection of solutions already used in hydroelectric plants with analogous technological solutions. The results were satisfactory in view of the periodicity of the use of the tool and the possibility of increasing the case base as the logics are implemented in other projects, besides allowing the inclusion of other logics and documentation pertinent to the Hydropower Plants.