Techno-Economic Analysis and Modelling of the Feasibility of Wind Energy in Kuwait

There continues to be significant attention and investment in wind power generation, which can supply a high percentage of the global demand for renewable energy if harvested efficiently. The research study is based on a techno-economic analysis of the feasibility of implementing wind power generation in Kuwait for 105 MW of electricity generation based on 50 wind turbines, which is a major requirement for clean energy. The study focused on three main areas of analysis and numerical modelling using the RETScreen software tool. The first area involved evaluating the performance and efficacy of generating wind power by collecting, analysing, and modelling data on observed wind levels, wind turbine operation, and wind power generation. The second area comprised an environmental impact report to assess the environmental benefits of implementing wind power. The third area involved economic analysis of installing wind power in Kuwait. The analysis was undertaken to determine the energy recovery time for wind energy and determine the mitigation of global warming and pollution levels, the decrease of toxic emissions, and any cost savings from implementing clean energy systems in Kuwait. Additionally, sensitivity analysis was undertaken to determine the impact of certain variables in the modelling process. The results were used to estimate that the energy price would be $0.053 per kWh for a power generation capacity of 105 MWh based on an initial cost of US $168 million and O&M of $5 million for 214,000 MWh of electricity exported to the grid. Moreover, the wind turbine farm will potentially avoid the emission of approximately 1.8 million t of carbon dioxide per year, thereby saving about $9 million over 20 years spent through installing carbon capture systems for conventional power plants. The wind farm is estimated to have a payback time of 9.1 years.

Solar Photovoltaic System-Based Reduced Switch Multilevel Inverter for Improved Power Quality

This paper deals with a reduced switch multi-level inverter for the solar photovoltaic system-based 127-level multi-level inverter. The proposed technique uses the minimum number of switches to achieve the maximum steps in staircase AC output voltage when compared to the flying capacitor multi-level inverter, cascaded type multilevel inverter and diode clamped multi-level inverter. The use of a minimum number of switches decreases the cost of the system. To eliminate the switching losses, in this topology a square wave switch is used instead of pulse width modulation. Thereby the total harmonic distortion (THD) and harmonics have been reduced in the pulsating AC output voltage waveform. The performance of 127-level MLI is compared with 15 level, 31-level and 63-level multilevel inverters. The outcomes of the solar photovoltaic system-based 127-level multi-level inverter have been simulated in a MATLAB R2009b environment.

Hydrogen as a Clean and Sustainable Energy Vector for Global Transition from Fossil-Based to Zero-Carbon

Hydrogen is recognized as a promising and attractive energy carrier to decarbonize the sectors responsible for global warming, such as electricity production, industry, and transportation. However, although hydrogen releases only water as a result of its reaction with oxygen through a fuel cell, the hydrogen production pathway is currently a challenging issue since hydrogen is produced mainly from thermochemical processes (natural gas reforming, coal gasification). On the other hand, hydrogen production through water electrolysis has attracted a lot of attention as a means to reduce greenhouse gas emissions by using low-carbon sources such as renewable energy (solar, wind, hydro) and nuclear energy. In this context, by providing an environmentally-friendly fuel instead of the currently-used fuels (unleaded petrol, gasoline, kerosene), hydrogen can be used in various applications such as transportation (aircraft, boat, vehicle, and train), energy storage, industry, medicine, and power-to-gas. This article aims to provide an overview of the main hydrogen applications (including present and future) while examining funding and barriers to building a prosperous future for the nation by addressing all the critical challenges met in all energy sectors.

Analyzing the Applicability of Random Forest-Based Models for the Forecast of Run-of-River Hydropower Generation

Analyzing the impact of climate variables into the operational planning processes is essential for the robust implementation of a sustainable power system. This paper deals with the modeling of the run-of-river hydropower production based on climate variables on the European scale. A better understanding of future run-of-river generation patterns has important implications for power systems with increasing shares of solar and wind power. Run-of-river plants are less intermittent than solar or wind but also less dispatchable than dams with storage capacity. However, translating time series of climate data (precipitation and air temperature) into time series of run-of-river-based hydropower generation is not an easy task as it is necessary to capture the complex relationship between the availability of water and the generation of electricity. This task is also more complex when performed for a large interconnected area. In this work, a model is built for several European countries by using machine learning techniques. In particular, we compare the accuracy of models based on the Random Forest algorithm and show that a more accurate model is obtained when a finer spatial resolution of climate data is introduced. We then discuss the practical applicability of a machine learning model for the medium term forecasts and show that some very context specific but influential events are hard to capture.

A Conceptual Framework for Biointelligent Production—Calling for Systemic Life Cycle Thinking in Cellular Units

A sustainable design of production systems is essential for the future viability of the economy. In this context, biointelligent production systems (BIS) are currently considered one of the most innovative paths for a comprehensive reorientation of existing industrial patterns. BIS are intended to enable a highly localized on-demand production of personalized goods via stand-alone non-expert systems. Recent studies in this field have primarily adopted a technical perspective; this paper addresses the larger picture by discussing the essential issues of integrated production system design. Following a normative logic, we introduce the basic principle of systemic life cycle thinking in cellular units as the foundation of a management framework for BIS. Thereupon, we develop a coherent theoretical model of a future decentralized production system and derive perspectives for future research and development in key areas of management.

Hardware Implementation of Composite Control Strategy for Wind-PV-Battery Hybrid Off-Grid Power Generation System

In this paper, a composite control strategy for improved off-grid configuration based on photovoltaic (PV array), a wind turbine (WT), and a diesel engine (DE) generator to achieve high performance while supplying nonlinear loads is investigated. To operate the WT efficiently under variable speed conditions and to obtain accurate and fast convergence to the maximum global operating point without a speed sensor, an iterative interpolation method is integrated with the perturbation and observation (P&O) technique. To ensure the balance of power in the system and to achieve the maximum power from the PV array without using any maximum power point tracking (MPPT) method, and ensuring stable operation during the disturbance, a double-loop control strategy for a two-switches buck-boost converter is developed. Furthermore, to protect the synchronous generator of the diesel generator (DG) from the 5th and 7th order-harmonics created by the connected nonlinear loads and to solve the issue of the filter resonance, the interfacing three-phase inverter is controlled using an improved synchronous-reference frame algorithm (SRF) with virtual impedance active damping. The presented work demonstrates effective and efficient control along with improved performance and cost-effective option as compared to the similar works reported in the literature. The performance of the presented off-grid configuration and its developed composite control strategy are tested using MATLAB/Simulink and validated through small-scale hardware prototyping.

Isolation Microgrid Design for Remote Areas with the Integration of Renewable Energy: A Case Study of Con Dao Island in Vietnam

In remote areas, extending a power line to the primary electricity grid can be very expensive and power losses are high, making connections to the grid almost impossible. A well-designed microgrid that integrates renewable energy resources can help remote areas reduce investment costs and power losses while providing a reliable power source. Therefore, investigating the design of an independent and economically practical microgrid system for these areas is necessary and plays an important role. This paper introduces a design procedure to design an isolated microgrid using HOMER software for remote areas. In Vietnam, due to the obstruction of the mountainous terrain or the isolated island location, many remote areas or islands need electrification. A simple case study of a hybrid system with a 60 kW peak load demand on Con Dao island in Vietnam is used to illustrate the proposed design method. Specifically, a hybrid system that includes a PV system, batteries, and a diesel generator is designed. To provide the full information of the designed hybrid system designed, each solution is analyzed and evaluated in detail according to the sensitivity parameters.

Estimating Smart Wi-Fi Thermostat-Enabled Thermal Comfort Control Savings for Any Residence

Nowadays, most indoor cooling control strategies are based solely on the dry-bulb temperature, which is not close to a guarantee of thermal comfort of occupants. Prior research has shown cooling energy savings from use of a thermal comfort control methodology ranging from 10 to 85%. The present research advances prior research to enable thermal comfort control in residential buildings using a smart Wi-Fi thermostat. “Fanger’s Predicted Mean Vote model” is used to define thermal comfort. A machine learning model leveraging historical smart Wi-Fi thermostat data and outdoor temperature is trained to predict indoor temperature. A Long Short-Term-Memory neural network algorithm is employed for this purpose. The model considers solar heat input estimations to a residence as input features. The results show that this approach yields a substantially improved ability to accurately model and predict indoor temperature. Secondly, it enables a more accurate estimation of potential savings from thermal comfort control. Cooling energy savings ranging from 33 to 47% are estimated based upon real data for variable energy effectiveness and solar exposed residences.

Key Targets for Improving Algal Biofuel Production

A number of technological challenges need to be overcome if algae are to be utilized for commercial fuel production. Current economic assessment is largely based on laboratory scale up or commercial systems geared to the production of high value products, since no industrial scale plant exits that are dedicated to algal biofuel. For macroalgae (‘seaweeds’), the most promising processes are anaerobic digestion for biomethane production and fermentation for bioethanol, the latter with levels exceeding those from sugar cane. Currently, both processes could be enhanced by increasing the rate of degradation of the complex polysaccharide cell walls to generate fermentable sugars using specifically tailored hydrolytic enzymes. For microalgal biofuel production, open raceway ponds are more cost-effective than photobioreactors, with CO2 and harvesting/dewatering costs estimated to be ~50% and up to 15% of total costs, respectively. These costs need to be reduced by an order of magnitude if algal biodiesel is to compete with petroleum. Improved economics could be achieved by using a low-cost water supply supplemented with high glucose and nutrients from food grade industrial wastewater and using more efficient flocculation methods and CO2 from power plants. Solar radiation of not <3000 h·yr−1 favours production sites 30° north or south of the equator and should use marginal land with flat topography near oceans. Possible geographical sites are discussed. In terms of biomass conversion, advances in wet technologies such as hydrothermal liquefaction, anaerobic digestion, and transesterification for algal biodiesel are presented and how these can be integrated into a biorefinery are discussed.

Comparative Life Cycle Assessment of EPA and DHA Production from Microalgae and Farmed Fish

The present study aims at comparing the life cycle environmental impacts of polyunsaturated fatty acids production (PUFA) from microalgae and farmed fish. PUFA production from microalgae cultivated via heterotrophy and photoautotrophy was assessed and compared. The primary energy demand (PED) and environmental impacts (EI) of PUFA production from microalgae via heterotrophy were significantly lower compared to PUFA produced via photoautotrophy. Furthermore, PED and EI of PUFA production from fish farmed in marine net pens were assessed. The results indicated that the PED and EI of PUFA production from farmed fish are higher than that produced from microalgae cultivated via heterotrophy. Therefore, the results suggest that PUFA produced from microalgae via heterotrophy could substitute fish oil from an environmental perspective. Furthermore, life cycle analysis results indicate that PUFA derived from microalgae could potentially replace fish oil in the fish feed, thus reducing the pressure on oceans.