Journal of Energy Management and Technology
Volume:5 Issue: 4, Autumn 2021

Rural electrification by the main grid entails large investments and losses. For this, the use of a decentralized energy system such as biomass is very interesting. The main objective of this article is to assess the technico-economic performance of the biomass energy electrical system designed for the electrification of a remote rural area by presenting a Tunisian residential case study located in a north-eastern region.Thus, a mathematical programming model was developed to determine the optimal radius to cultivate allowing the reduction of the cost of MWh allowing maximizing the profit index PI. The economic efficiency of the biomass energy system is proven by results under operating conditions specified in the study such as the number of consumers and the price of the biomass energy system indicated by Is. This preliminary study of the electrical consumption of a case study allowed us to highlight the influence of the quantity of electrical energy consumed as well as the specific investment on the profit index.

The need for diversified energy resources, sustainable development, energy security and improving the reliability of electrical energy systems, have led to serious global attention to the development and expansion of small-scale power plants better known as distributed generation (DG) and increase the share of these resources in the global energy basket. One of the problems for the power supply of subway systems, is that it is difficult to supply the energy they need using the utility grid due to their passage through crowded centers. This requires the construction of power posts by the company in charge of building the metro systems which requires a lot of costs for the company. Therefore, alternative ways of supplying energy for the metro system can be sought. One way is to use small-scale local power plants. The use of these energy sources can achieve benefits such as higher economic productivity, greater reliability and better management of fluctuations. Therefore, in this paper, the issue of using distributed energy sources for the metro system is examined. The proposed framework for effective and efficient resource development, along with long-term planning of the system components, management and intelligent use of these resources to provide the power supply of the subway, in the field of short-term operation also includes. Purchase prices from the upstream network have been considered and the net present value (NPV) and investment costs have been studied using engineering economics methods. The uncertainty of demand levels in traction buses are modeled using chance constrained programming (CCP). By means of CCP approach, better decisions without jeopardizing the security of the system, can be made. Finally, using GAMS and DigSilent softwares, the problem is optimized and the technical parameters are examined for practical Tabriz subway system test system.

Wind power uncertainty is one of the problems in large-scale wind farms integration to the network. The use of Energy Storage Systems (ESSs) is a practical solution to enhance availability and power dispatching possibility of renewable energy sources (RESs). RESs need an ESS with high power and energy capacity while none of ESSs has this feature at the same time. The accepted solution for this problem is using the hybrid energy storage system (HESS). In this paper, HESS optimal sizing and power dispatching of wind-HESS system are considered, simultaneously, and the problem of high storage capacity in the modified min-max wind power dispatching method is resolved by utilizing the limited min-max wind power dispatching method. The optimal types and capacity of HESS are determined based on multi-objective optimization function with objectives of maximizing the net present value and storage lifetime. Furthermore, in short-term power management control, the wind-HESS performance and delivering the prescheduled and constant power to the network are investigated and HESS charge-discharge cycles are controlled to work in safety range. Finally, the proposed method and short-term power management are evaluated by a wind farm real data, which is scaled down to 3 MW power level for better comparison with other studies.

This study has conducted on developing an innovative approach for the parametric analysis of daylighting and visual comfort through a sun responsive shading system as well as proposed a parametric pattern of Iranian Traditional Girih Tile (ITGT). On this basis, using parametric methods, the authors could change the parameters of a pattern to build modern geometric patterns and a bridge between traditional architecture approaches and modern technologies. The model was simulated in the Rhinoceros 3D as well as the Grasshopper, Honeybee, and Ladybug plugins were performed in order to evaluate daylighting and visual comfort performance. The objectives are estimating the annual daylight metrics and glare discomfort during four months from spring to summer when 3 variables (opening and getting closed, mass to space ratio, and time hours) that affect incoming daylight and visual comfort performance in a room. The results showed that the proposed model could significantly improve the shading flexibility to control daylight metrics and glare, through a full potential adaptive pattern to achieve the maximum visual comfort.

Energy is one of the most important and basic needs in human life. Due to the high share of energy consumption in residential buildings, an important need to optimize energy consumption in this field is felt. In between, the role of building shell is very important, because it can play a pivotal role in this field and reduce energy consumption. In this research, initially different types of insulations used in various buildings were examined and classified. Determination of the physical and thermal characteristics of each material lead to the selection of the appropriate options. Finally, a simulation is performed using the EnergyPlus software to measure the efficiency of said materials in different roles. The work method is that first a building with all the standard specifications is designed in the software environment. The simulation is then done using the EnergyPlus software for different time periods and climate conditions in Tehran and the results are obtained. Moreover, by adding effective insulations to reduce energy consumption and re-simulation, the effect of each of them is analyzed. The results of this research show the reduction of energy consumption by up to 30%.

By increasing the penetration of renewable energy sources with probabilistic nature, the power system is faced with operating and management challenges. Therefore, employing coordinated energy storage systems is a great choice that could better deal with inherent uncertainties. This paper proposes an optimal bidding strategy for an integrated wind power plant coordinated with energy storage systems consist of compressed air energy storage and power to the gas facility to participate in the day-ahead market. In addition, to mitigate wind energy fluctuation by charging and discharging schemes, excess wind power can be stored and converted to natural gas based on gas condition prices through the power to the gas facility. The proposed bidding strategy is formulated as a hybrid stochastic-robust optimization approach, in which the wind power uncertainty is modeled by scenario-based stochastic method, while day-ahead electricity prices are handled via robust optimization approach, with the aim of profit maximization. Thereafter, based on the optimal charging and discharging scheme, the hourly bidding and offering curves are generated. Numerical results reveal the effectiveness of the proposed model in the mitigation of wind energy curtailment and profit maximization

This study discusses a new approach to demand response program scheduling (DRP) having retail electricity providers (REPs) with lighter tangible assets. The primary goal of this study is to present an optimal multi-objective function design for integrating REPs into a motivational DRP, while taking into account uncertainty of loads and LMP (location marginal prices). Designing with fuzzy functions are used for load uncertainty and Non-dominated sorting genetic algorithm (NSGA-II) is implemented to find solutions. The optimal compatibility between Pareto front-generated solutions was achieved by using a fuzzy, non-linear attribution method. In order to demonstrate the performance of the proposed model, simulations are performed on the IEEE 24 bus RTS test system. The results have shown that short-run benefits of REPs in electricity markets could be provided and ensured through the designed DRPs. In this paper, the short-term scheduling for DRP with asset-light retailers is proposed. The main idea is to determine an optimal for these retail electricity providers to cooperate cooperate with them and propose the optimal DRP base on the incentive in the market while having short-time benefits and load uncertainties in mind on locational marginal prices (LMP).It is assumed that the DISTCO’s do not participate in the DRP, and only REPs and consumers are involved. Short DRP schedules for light-asset retailers providing electricity for customers use a multi-objective optimization design with practical restrictions in performance. Short-term DRP scheduling of the light-asset retailers who provide the electricity consumers is formulated through a multi-objective optimization model with practical operational constraints.