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Grid interconnected multi-microgrids provides potential benefits to the consumers, where the microgrids (MGs) equipped with distributed generators (DGs), energy storage systems (ESSs), and diesel generators. However, intermittency of DGs, high cost of ESSs, and depleting fossil fuels are the major challenges for the economic operation of interconnected multi-microgrids. One potential way to address these challenges is to develop an energy management strategy (EMS) for the grid interconnected multi-microgrids. This paper proposes an EMS to reduce consumer energy consumption cost (ECC) using fuzzy-based peer-to-peer (P2P) energy exchange algorithm with dynamic pricing. In this context, the MGs consumers load power demand (LPD) and DGs output behaviors are modeled using random vector functional link network approach to predict future time slot values. Then, a fuzzy-based P2P energy exchange algorithm is developed to enable the surplus energy transfer to grid and/or MGs with dynamic pricing. Furthermore, an ESS charging/discharging energy control and diesel generator turn on strategies are developed based on the MGs deficit power. Then, the MGs consumer LPD reduction strategy is implemented based on the consumer ECC margin and energy consumption index. Finally, an EMS is proposed that includes on demand-supply strategy and consumer energy consumption cost reduction strategy based on the future time slot values. The novelty of the proposed work lies within the energy management of grid interconnected multi-microgrids and the reduction of consumers ECC through surplus energy transfer to grid and/or MGs using fuzzy-based P2P energy exchange algorithm with dynamic pricing. Historical data are used to demonstrate the effectiveness of the proposed EMS for grid interconnected multi-microgrids.

In this paper, we propose mathematical optimization models of household energy units to optimally control the major residential energy loads while preserving the user preferences. User comfort is modelled in a simple way, which considers appliance class, user preferences and weather conditions. The wind-driven optimization (WDO) algorithm with the objective function of comfort maximization along with minimum electricity cost is defined and implemented. On the other hand, for maximum electricity bill and peak reduction, min-max regret-based knapsack problem (K-WDO) algorithm is used. To validate the effectiveness of the proposed algorithms, extensive simulations are conducted for several scenarios. The simulations show that the proposed algorithms provide with the best optimal results with a fast convergence rate, as compared to the existing techniques.

Energy sector decarbonization to limit the temperature rise to well-below 2°C will result in stranded assets and capital stock replacement before its technical lifetime ends. In this paper, strande...

Due to limited fossil fuel resources, a growing increase in energy demand and the need to maintain positive environmental effects, concentrating solar power (CSP) plant as a promising technology has driven the world to find new sustainable and competitive methods for energy production. The scheduling capability of a CSP plant equipped with thermal energy storage (TES) surpasses a photovoltaic (PV) unit and augments the sustainability of energy system performance. However, restricting CSP plant application compared to a PV plant due to its high investment is a challenging issue. This paper presents a model to assemble a combined heat and power (CHP) with a CSP plant for enhancing heat utilization and reduce the overall cost of the plant, thus, the CSP benefits proved by researches can be implemented more economically. Moreover, the compressed air energy storage (CAES) is used with a CSP-TES-CHP plant in order that the thermoelectric decoupling of the CHP be facilitated. Therefore, the virtual power plant (VPP) created is a suitable design for large power grids, which can trade heat and electricity in response to the market without restraint by thermoelectric constraint. Furthermore, the day-ahead offering strategy of the VPP is modeled as a mixed integer linear programming (MILP) problem with the goal of maximizing the profit in the market. The simulation results prove the efficiency of the proposed model. The proposed VPP has a 2% increase in profit and a maximum 6% increase in the market electricity price per day compared to the system without CAES.

In recent years, China has promoted a series of legal norms to reduce the environmental impact of air pollutants from vehicles. The three main vehicle emission species (carbon monoxide, hydrocarbons, nitrogen oxides) contribute significantly to air pollution. In this study, the emission factor method was used to estimate air pollutants from vehicles in 31 provinces from 2006 to 2016. The results show a trend of total vehicle carbon monoxide (CO) and hydrocarbons (HC) emissions decreasing with time; the vehicle nitrogen oxides (NOx) emission trend is divided into two stages: an upward trend between 2006 and 2012 and a downward trend after 2012. Based on a panel threshold, a regression method was used to divide the vehicle NOx and CO emissions in China into four emission zones: low emissions, medium emissions, high emissions, and extra-high emissions. Vehicle HC emissions were divided into three emission zones, which corresponded to low emissions, medium emissions, and high emissions. Overall, vehicle pollution emission efficiency and per capita GDP have a significant inhibitory effect on the three main air pollutants from vehicles (NOx, HC, CO). Both passenger and freight turnover have significant roles in promoting the three air pollutants from vehicles (NOx, HC, CO). Road density and road carrying capacity have a significant role in promoting vehicle HC and CO emissions. Increasing truck proportion inhibits vehicle CO emissions and promotes vehicle NOx emissions. The urbanization rate has a positive effect on vehicle HC and CO emissions. Moreover, there is obvious heterogeneity in different emission zones of the three air pollutants from vehicles (NOx, HC, CO).

The component count for the multilevel inverter has been a research topic for the last few decades. The higher number of power semiconductor devices and sources leads to a higher power loss with the complex control requirement. A new multilevel inverter topology employing the concept of half-Bridge modules is suggested in this paper. It requires a lower number of dc sources and power components. The inverter is controlled using a fundamental frequency switching scheme. With the basic unit being able to produce 13 level voltage waveforms with three dc voltage sources, higher-level inverter configuration has also been discussed in the paper. The performance of the topology is analyzed in the aspects of circuit parameters and found better when compared to similar topologies proposed in recent literature. The comparison provided in the paper set the benchmark of the proposed topology in terms of lower component requirements. The topology is also optimized with two voltage fixing algorithms for maximizing the number of levels for the given number of IGBTs, drivers and dc sources, and the observations are presented. The efficiency analysis gives the peak efficiency as 98.5%. The simulations were carried out using the PLECS software tool and validated using a prototype rated at 500 W. The results with several test conditions have been reported and discussed in the paper.

<p>Indoor air quality as always is the centre of attention for researchers, architect developers and public health officials. As every-one know. The human exposure to a variety of indoor pollutants and the high cost of energy are the motivation for these kinds of studies. Fungus and mould growth has always been a problem in subtropical climate areas due to the high temperature and high humidity. Generally in institutional buildings, most of the internal heat load is generated by human body and thermal comfort is achieved with extensive usage of recycled air and air conditioning. The main considerations in any air conditioning system economisers are based on the usage of recycled air and air ventilation. The current practice in an institutional building cooling system under subtropical climate is to curb the mould issue by overcooling large recirculation airflow to remove the moisture content from the air, which is considered as an expensive practice. The use of a solar desiccant cooling system to reduce moisture from the air and to improve indoor air quality is found to be economical, environmental friendly and readily achievable in the tropics. This technology is the future alternative to the conventional vapour compression cooling system to maintain human thermal comfort conditions and enhance indoor air quality. Solar desiccant cooling systems are also environmentally friendly and energy efficient. This paper presents review on a solar desiccant cooling system and its effect on indoor air quality. It first introduces the issue of air moisture, mould growth and indoor air quality and then the development and application of thermally activated desiccant cooling technologies.</p>

© 2015 The Authors. The UAE per capita energy consumption is one of the highest in the world. Since the energy sector is the center of most ecological problems facing the world today, eco-efficiency and eco-innovations are at the top of the sustainability agenda in most countries. The UAE "Green Economy for Sustainable Development" (2012-2021) aims to position the country as a center for the export and re-export of green products and technologies. In light of the above, the focus of this paper is to present a smart plug system for monitoring and controlling household energy consumption using a mobile application. The smart plug system is an essential component in smart grids as it provides real-time high-resolution information for distribution companies to aid them in decision-making. In addition, the study measures the perceived usefulness and satisfaction of the smart plug system and its mobile application in the UAE. The paper makes an important theoretical contribution by including environmental concern as an additional variable to a well-established information systems success model. Our findings suggest that the smart plug system provides users with convenient access to information regarding their personal energy consumption and allows them to control their per capital energy consumptions via the mobile application at very low costs. Further, we validated our theoretical model using structural equation modeling and conclude that environmental concern has an indirect impact on the perceived satisfaction and both an indirect and a direct impact on the perceived usefulness of the smart plug system. The practical implications of our study suggest that per capita energy consumption is likely to significantly decrease with wide adoption of the smart plug system in the UAE.