On the Applicability of Two Families of Cubic Techniques for Power Flow Analysis

This work presents a comprehensive analysis of two cubic techniques for Power Flow (PF) studies. In this regard, the families of Weerakoon‐like and Darvishi‐like techniques are considered. Several theoretical findings are presented and posteriorly confirmed by multiple numerical results. Based on the obtained results, the Weerakoon’s technique is considered more reliable than the New‐ ton‐Raphson and Darvishi’s methods. As counterpart, it presents a high computational burden. Re‐ garding this point, the Darvishi’s technique has turned out to be quite efficient and fully competitive with the Newton’s schem

Home energy management system considering effective demand response strategies and uncertainties

Nowadays, load serving entities require more active participation from consumers. In this context, demand response programs and home energy management systems play a crucial role in achieving multiple goals such as peak clipping. However, the adoption of demand response initiatives typically has a negative impact on the monetary expenditures of the users. This way, a demand response program should be as effective as possible to make the different goals more easily achievable without compromising the financial requirements of the users. This paper develops a home energy management system that incorporates three novel effective demand response strategies. The effectiveness of the adopted demand response strategies is checked through extensive simulations in a benchmark prosumer environment. To this end, a novel scenario-based approach is developed in order to manage uncertainties. The introduced strategies are compared with other well-known demand response mechanisms. To that end, a novel comparative index, which serves to evaluate the compromise between demand response achievements and energy bills, is introduced. Results obtained demonstrate that the developed strategies are more effective than other approaches. In fact, through the use of the proposed mechanisms, different indicators can be improved until ∼70%, while the electricity bill is only scarcely increased (∼0.11€). Other relevant aspects like the influence of the storage capacity and computational performance of the introduced optimization framework are also analysed

An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks

This paper introduces a novel technique for optimal distribution system (DS) planning with distributed generation (DG) systems. It is being done to see how active and reactive power injections affect the system’s voltage profile and energy losses. DG penetration in the power systems is one approach that has several advantages such as peak savings, loss lessening, voltage profile amelioration. It also intends to increase system reliability, stability, and security. The main goal of optimal distributed generation (ODG) is a guarantee to achieve the benefits mentioned previously to increase the overall system efficiency. For extremely vast and complicated systems, analytical approaches are not suitable and insufficient. Therefore, several meta-heuristic techniques are favored to obtain better performance from were convergence and accuracy for large systems. In this paper, an Improved Wild Horse Optimization algorithm (IWHO) is proposed as a novel metaheuristic method for solving optimization issues in electrical power systems. IWHO is devised with inspirations from the social life behavior of wild horses. The suggested method is based on the horse’s decency. To assess the efficacy of the IWHO, it is implemented on the 23 benchmark functions Reliability amelioration is the most things superb as a result of DGs incorporation. Thus, in this research, a customer-side reliability appraisal in the DS that having a DG unit was carried out by a Monte Carlo Simulation (MCS) approach to construct an artificial history for each ingredient across simulation duration. For load flow calculations, the backward Forward Sweep (BFS) technique has been employed as a simulation tool to assess the network performance considering the power handling restrictions. The proposed IWHO method has been measured on IEEE 33 69 and 119 buses to ascertain the network performing in the presence of the optimal DG and the potential benefits of the suggested technique for enhancing the tools used by operators and planners to maintain the system reliability and efficiency. The results proved that IWHO is an optimization method with lofty performance regarding the exploration–exploitation balance and convergence speed, as it successfully handles complicated problems

An Experimental Study of Power Smoothing Methods to Reduce Renewable Sources Fluctuations Using Supercapacitors and Lithium-Ion Batteries

The random nature of renewable sources causes power fluctuations affecting the stability in the utility grid. This problem has motivated the development of new power smoothing techniques using supercapacitors and batteries. However, experimental studies based on multiple renewable sources (photovoltaic, wind, hydrokinetic) that demonstrate the validity of power smoothing techniques under real conditions still require further study. For this reason, this article presents a feasibility study of a renewable grid-connected system, addressing various aspects based on power quality and energy management. The first of them is related to the fluctuations produced by the stochastic characteristics of renewable sources and demand. Two power smoothing algorithms are presented (ramp rate and moving average) combining photovoltaic, wind, and hydrokinetic sources with a hybrid storage system composed of supercapacitors and lithium-ion batteries. Then, the self-consumption for an industrial load is analyzed by studying the energy flows between the hybrid renewable energy sources and the grid. The main novelty of this paper is the operability of the supercapacitor. The experimental results show that when applying the power smoothing ramp rate method, the supercapacitor operates fewer cycles with respect to the moving average method. This result is maintained by varying the capacity of the renewable sources. Moreover, by increasing the capacity of photovoltaic and wind renewable sources, the hybrid storage system requires a greater capacity only of supercapacitors, while by increasing the capacity of hydrokinetic turbines, the battery requirement increases considerably. Finally, the cost of energy and self-consumption reach maximum values by increasing the capacity of the hydrokinetic turbines and batteriesPartial funding for open access charge: Universidad de Málag

An insight into the integration of distributed energy resources and energy storage systems with smart distribution networks using demand-side management

Demand-side management (DSM) is a significant component of the smart grid. DSM without sufficient generation capabilities cannot be realized; taking that concern into account, the integration of distributed energy resources (solar, wind, waste-to-energy, EV, or storage systems) has brought effective transformation and challenges to the smart grid. In this review article, it is noted that to overcome these issues, it is crucial to analyze demand-side management from the generation point of view in considering various operational constraints and objectives and identifying multiple factors that affect better planning, scheduling, and management. In this paper, gaps in the research and possible prospects are discussed briefly to provide a proper insight into the current implementation of DSM using distributed energy resources and storage. With the expectation of an increase in the adoption of various types of distributed generation, it is estimated that DSM operations can offer a valuable opportunity for customers and utility aggregators to become active participants in the scheduling, dispatch, and market-oriented trading of energy. This review of DSM will help develop better energy management strategies and reduce system uncertainties, variations, and constraints

Proton exchange membrane fuel cells: Recent advances, modeling, and future trends

The study of proton exchange membrane fuel cells (PEMFCs) has received great attention from the scientific community. The main objectives of research in this area are to reduce greenhouse gas emissions, especially in the automotive industry, and develop new techniques and materials to increase the efficiency of PEMFCs at a reasonable cost. In this regard, the development of high-performance polymeric membranes is presented together with nanomaterials with high catalytic activity and stability that work at low and moderate temperatures. Similarly, the development of new techniques or materials for electrodes and catalysts that allow the development of new improved water management techniques within PEMFCs is studied. This chapter examines recent advances and future trends in the modeling of PEMFCs and their components. In addition, it discusses the main applications of PEMFCs and presents current and projected statistical dat

Repowering Feasibility Study of a Current Hybrid Renewable System. Case Study, Galapagos Islands

Renewable sources on islands seem to be the most attractive option to decarbonize and lower the price of electricity; currently, most islands do so by replacing their diesel generators with wind or solar sources, along with energy storage. The Galapagos Islands are no exception. This study presents a techno-economic analysis of hybrid renewable systems in the Galapagos Islands, considering the repowering of its renewable sources and reduction in the penetration of diesel generators. This study uses EnergyPlan software, where the best option is chosen based on technical, economic, and environmental indicators. Finally, several sensitivity analyses are done. The results show that by increasing the capacity of current wind and photovoltaic systems, the total annual cost reduces by 20% and 10.31%, respectively; this is a specific result of this study. Moreover, there is a reduction in CO2 emissions produced by diesel generators, up to 38.96%

Smart energy transition with the inclusion of floating wind energy in existing hydroelectric reservoirs with a view to 2050. Ecuadorian case study

Ecuador promotes an energy matrix with zero net emissions by 2050, knowing that hydroelectric power from a reservoir has been fundamental in the electrical system. The reservoirs comprise large unused areas, in many of these sites there are interesting wind speeds thanks to the wind tunnels that are formed between hill and hill and can be used by installing floating wind turbines. This research presents an alternative to increase the driving actions of Ecuador to structure its 100% renewable energy system in a diversified way. For this reason, the resulting impact is analyzed by including Floating Wind Power (FWP) systems and four points of interest are analyzed in this study: Mazar, Coca Codo Sinclair, Manduriacu and Delsitanisagua. The energy mix is evaluated using EnergyPLAN software, a specialized tool to evaluate diversified smart systems of completely renewable electricity in the long term. This study is novel, breaks the traditional schemes in Ecuador and provides a different vision for decision makers, such as investors, legislators and researchers to discuss before committing economic resources. The results show that in 2050 floating wind energy would be contributing 11.13% of the total electricity in Ecuador and 16.27% of the wind component. Interpreting these values, the floating wind component may be significant and would further diversify energy production in this South American country

Intrinsic Characteristics of Forward Simulation Modeling Electric Vehicle for Energy Analysis

The forward method for modeling electric vehicles is one of the most suitable for estimating energy consumption in different imposed driving cycles. However, a detailed description of the methodology used for the development of electric vehicle models is necessary and is scarce in the current literature. To fill this gap, this study focuses on highlighting the intrinsic characteristics through a theoretical study with a mathematical model, complemented by demonstrative simulations in Matlab/Simulink. The results show that the forward method can be estimated more accurately based on the energy consumption of the electric vehicle. Moreover, this paper aims to be explicitly descriptive for the development of more complex electric vehicle models to incorporate real driving cycles, being able to size the drivetrain of the vehicle itself or develop ecological routes

Intrinsic Characteristics of Forward Simulation Modeling Electric Vehicle for Energy Analysis

The forward method for modeling electric vehicles is one of the most suitable for estimating energy consumption in different imposed driving cycles. However, a detailed description of the methodology used for the development of electric vehicle models is necessary and is scarce in the current literature. To fill this gap, this study focuses on highlighting the intrinsic characteristics through a theoretical study with a mathematical model, complemented by demonstrative simulations in Matlab/Simulink. The results show that the forward method can be estimated more accurately based on the energy consumption of the electric vehicle. Moreover, this paper aims to be explicitly descriptive for the development of more complex electric vehicle models to incorporate real driving cycles, being able to size the drivetrain of the vehicle itself or develop ecological routes