Today, renewable resources have become one of the main pillars of electricity generation because of the constant reduction in their costs. In this regard, wind energy possesses the highest share in installed capacity and total energy output. Adopting a well-structured planning model is one of the most effective ways to further reduce costs and been the focus of research in the past decades. The previously models use a generic model for the wind turbine and its related parameters while only the optimal number is determined. In this context, this paper presents a novel approach for optimally planning of wind-diesel-battery systems which optimizes the wind turbine technology as a decision variable from the different types already commercially available. For this purpose, an optimization problem is introduced with the possibility of choosing a single type of turbine technology. The proposed model is then modified to optimize and simultaneously select multiple different wind turbine technologies. Results of the case study demonstrate a significant reduction in the planning cost, namely above 5 percent depend on the wind speed. Furthermore, the total yearly energy generated by diesel generator is decreased by 700 kWh, meaning higher renewable penetration and less emissions.

Ever-increasing consumption of the electricity in the distribution networks encounters network planners with new challenges in terms of expansion requirements. Expanding substations is a technical concern considering various binding conditions. Emerging Battery Energy Storage Systems (BESSs) have the potential to defer substation expansion needs effectively. Although various applications of the BESSs are considered in the literature previously, application of the BESSs to defer substation expansion plans is not addressed adequately. In this context, this paper proposes a novel Multi-Objective Mixed Integer Linear Programming (MOMILP) for BESS operation in distribution networks to simultaneously substation expansion deferral and cost reduction. The proposed model is highly flexible with respect to the planner preferences, without convergence problems, and easily solvable using commercial solvers. The model determines charging and discharging scheduling of the active and reactive power of the BESSs optimally to achieve maximum substation expansion deferral without increasing operation costs. Higher degrees of the expansion deferral can be achieved at the expanse of the negligible cost increase. Furthermore, details of the whole BESS system including various parts and active/reactive power relations and limits are modeled accurately to better demonstrate real-life situations. Results of the simulations demonstrate accuracy and also functionality of the proposed method.

This paper addresses both the experimental and simulation studies on the application of overcurrent protective relay. The industrial overcurrent relays often have three individual settings. In this paper, the relay operating characteristics are set on normal inverse and very inverse curves. These curves operate as backup of each other. The third setting is also set on the instantaneous definite minimum time. The designated protection scheme protects the system with the least operating time.

The net-zero energy buildings are often supplied by renewable resources and energy storage systems. These energy resources have different seasonal and daily patterns of power production. Their output power is also uncertain. This paper aims to study these issues including daily-seasonal operation patterns, uncertainty, and cogeneration of various renewable resources and storage systems. These issues are investigated at net-zero energy building supported by renewable resources (i.e., solar energy, hydro energy, and fuelcell) and energy storage systems (i.e., hydrogen storage system). The uncertain parameters of the model are solar-hydro-load powers. The model minimizes the investment cost on solar system. The plan finds optimal sizing and operation for solar, hydro, hydrogen, and fuel-cell. The cooperation of hydrogen storage and fuelcell is optimized to level the uncertainty. The surplus of energy is fed into water electrolyzer to produce hydrogen and the fuelcell consumes the hydrogen to produce electricity. The seasonal operation is dealt by cogeneration of hydro-solar systems. The proposed plan installs 73 kW solar panel. The hydrogen storage system is charged at hours 7–17. When hydro power is increased to 39 kW, the building does not need the solar energy. The proposed model decreases the Carbon Dioxide by about 39546 kg. The model also reduces the total cost by about 50.3%.