Operation planning of an independent microgrid for cold regions by the distribution of fuel cells and water electrolyzers using a genetic algorithm

An energy system using a microgrid was examined in this work. The motivations for this study are to promote green energy usage, discuss concerns regarding energy supply during disasters, and improve the efficacy of waste heat usage. To create a society based on clean hydrogen energy, this paper studied the use of a microgrid to supply energy to six houses in a cold region. The proposed microgrid consisted of photovoltaics, a water electrolyzer, a fuel cell, and a heat pump; furthermore, this microgrid was not accompanied by any external energy supply. In this paper, the optimized calculation results obtained from the genetic algorithm (GA) were compared between a system operated using one set of large capacity equipment (a concentrated system) and a system operated using two or more pieces of distributed small-capacity equipment (a distributed system). From this comparison, the operation efficiency of each set of equipment was characterized using the difference in the load factor of the fuel cell and that of the water electrolyzer of each system. Moreover, the optimal capacities of the solar cell, fuel cells, water electrolyzers, and heat pumps while operating an energy-independent microgrid with the concentrated system and the distributed system were presented.     

Exergy,exergoeconomic and multi-objective optimization of a clean hydrogen and electricity production using geothermal-driven energy systems

In this research paper, comprehensive thermodynamic modeling of an integrated energy system consisting of a multi-effect desalination system, geothermal energy system, and hydrogen production unit is considered and the system performance is investigated. The system's primary fuel is a geothermal two-phase flow. The system consists of a single flash steam-based power system, ORC, double effect water–lithium bromide absorption cooling system, PEM electrolyzer, and MED with six effects. The effect of numerous design parameters such as geothermal temperature and pressure on the net power of steam turbine and ORC cycle, the cooling capacity of an absorption chiller, the amount of produced hydrogen in PEM electrolyzer, the mass flow rate of distillate water from MED and the total cost rate of the system are studied. The simulation is carried out by both EES and Matlab software. The results indicate the key role of geothermal temperature and show that both total exergy efficiency and total cost rate of the system elevate with increasing geothermal temperature. Also, the impact of changing absorption chiller parameters like evaporator and absorber temperatures on the COP and GOR of the system is investigated. Since some of these parameters have various effects on cost and efficiency as objective functions, a multi-objective optimization is applied based on a Genetic algorithm for this system and a Pareto-Frontier diagram is presented. The results show that geothermal main temperature has a significant effect on both system exergy efficiency and cost of the system. An increase in this temperature from 260 C to 300 C can increase the exergy efficiency of the system for an average of 12% at various working pressure and also increase the cost of the system by 13%.     

Predicting and presenting plausible future scenarios of wind power production from numerical weather prediction systems: a qualitative ex ante evaluation for decision making

This paper is concerned with evaluating techniques to forecast plausible future scenarios in wind power production for up to 48 h ahead, where the term scenario refers to a coherent chronological prediction including the timing, rapidity and size of large changes. Such predictions are of great interest in power systems with high regional wind penetration where a large rapid change in wind power may pose a threat to power system security. Numerous studies have evaluated wind power forecasting methods on ex post statistical measures of forecast accuracy such as root mean square error. Other work has assessed the forecast value by simulating automated decision making for bidding wind generation into particular electricity markets, and in some cases, the ex ante value of a perfect forecast has been assessed. The future, however, will always be uncertain, and decision making always takes place in an ex ante context. This paper discusses how numerical weather prediction (NWP) systems forecasts are produced, with a particular focus on uncertainty and how forecasters might visually present plausible future scenarios for wind power to electricity industry decision makers. It is difficult to quantify the ex ante value of visual wind power forecast information to the complex decision‐making process involved. Consequently, this paper explores qualitative assessments of ex ante value by proposing six desirable attributes for the techniques and the presentation of NWP forecasts to decision makers. It uses these attributes to assess four such methodologies, which include NWP ensemble methods and the recently introduced NWP spatial field approach. Copyright © 2011 John Wiley & Sons, Ltd.