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Following the societal electrification trend, airports face an inevitable transition of increased electric demand,driven by electric vehicles (EVs) and the potential rise of electric aviation (EA). For aviation, short-haul flightsare first in line for fuel exchange to electrified transportation. This work studies the airport of Visby, Sweden and the effect on the electrical power system from EA and EV charging. It uses the measured airport loaddemand from one year’s operation and simulated EA and EV charging profiles. Solar photovoltaic (PV) and electrical battery energy storage systems (BESS) are modelled to analyse the potential techno-economical gains.The BESS charge and discharge control are modelled in four ways, including a novel multi-objective (MO) dispatch to combine self-consumption (SC) enhancement and peak power shaving. Each model scenario iscompared for peak power shaving ability, SC rate and pay-back-period (PBP). The BESS controls are alsoevaluated for annual degradation and associated cost. The results show that the novel MO dispatch performswell for peak shaving and SC, effectively reducing the BESS’s idle periods. The MO dispatch also results in the battery controls’ lowest PBP (6.9 years) using the nominal economic parameters. Furthermore, a sensitivityanalysis for the PBP shows that the peak power tariff significantly influences the PBP for BESS investment.

Transport electrification continuously increases globally and propagates to new, even-larger vehicle applications due to decreased costs, battery technology improvements, and charging infrastructure rollout. This work highlights the importance of strategic planning for large electric vehicle charging nodes, like depots, terminals, airports and ports. Specifically from the perspective of predicting future power requirements and how to satisfy energy demand using a combination of smart charging algorithms, local photovoltaic electricity production and battery energy storage systems. A case study is presented where developed tools and models are applied to an airport for high-power charging of future electric aircraft.

Denna handbok beskriver relevansen av och tillvägagångssättet att planera och förvalta solcellsparker att gynna biologisk mångfald och ekosystemtjänster, med särskild fokus på jordbruk. Med utgångspunkten i hänsynshierarkin beskrivs hur målet om netto noll eller netto positiv påverkan kan integreras i solcellsprojektens olika faser. Centralt är att placeringar på mark med höga naturvärden ska undvikas. Planeringsfasen för nya solcellsparker behöver ta avstamp i de lokala förutsättningarna avseende befintliga naturvärden, potentialen för jordbruk och sociala och rekreativa värden. Sedan ska solcellsparken utformas så att solelproduktion och biologisk mångfald, jordbruk och/eller andra ekosystemtjänster kan samexistera. Detta kan underlättas genom zonindelningar och val av lämplig solcellsmontering och lämpliga solcellspaneler. Även framtagande av skötselplaner i ett tidigt skede bidrar till en anläggning som har goda förutsättningar att skapa multifunktionella värden. Anläggningsfasen ska utföras så att minimal påverkan sker på naturen och marken, till exempel genom att undvika vissa årstider, att hålla skyddsavstånd och undvika markpackning. Driftfasen handlar om rätt skötsel, så att den önskade biologiska mångfalden kan frodas och/eller att jordbruket är produktivt och att de olika aktiviteter kan hanteras effektivt sida vid sida. För att inspirera och ge konkret guidning innehåller handboken åtgärdsbibliotek för ekovoltaiska system (d.v.s. kombinationer av ökad biologisk mångfald och reglerande, kulturella och/eller stödjande ekosystemtjänster med solcellsinstallationer) och agrivoltaiska system. Solcellstekniska lösningar och deras påverkan på förutsättningar för framförallt jordbruk, men även biologisk mångfald, beskrivs också i mer detalj i handboken., Denna handbok har tagits fram inom projektet Eko-Sol, som finansierats av Energimyndigheten

Design and performance of polygeneration energy systems are highly influenced by several variables, including the climate zone, which can affect the load profile as well as the availability of renewable energy sources. To investigate the effects, in this study, the design of a polygeneration system for identical residential buildings that are located in three different climate zones in Iran has been investigated. To perform the study, a model has previously developed by the author is used. The performance of the polygeneration system in terms of energy, economy and environment were compared to each other. The results show significant energetic and environmental benefits of the implementation of polygeneration systems in Iran, especially in the building that is located in a hot climate, with a high cooling demand and a low heating demand. Optimal polygeneration system for an identical building has achieved a 27% carbon dioxide emission reduction in the cold climate, while this value is around 41% in the hot climate. However, when considering the price of electricity and gas in the current energy market in Iran, none of the systems are feasible and financial support mechanisms or other incentives are required to promote the application of decentralized polygeneration energy systems., QC 20180530

Small-scale decentralized polygeneration systems have several energetic, economic and environmental benefits. However, using multiple energy sources and providing multiple energy services can lead to complicated studies which require advanced optimization techniques for determining optimal solutions. Furthermore, several parameters can influence the design and performance of a polygeneration system. In this study, the effects of heat load, renewable generation and storage units on the optimal design and performance of a polygeneration system for a hypothetical hospital located in northern Italy are investigated. The polygeneration system shows higher performance compared to the reference system, which is based on the separate generation of heat and power. It reduces fuel consumption by 14-32%, CO2 emissions by 10-29% and annualized total cost by 7-19%, for various studied scenarios. The avoided fuel and electricity purchase of the polygeneration system has a positive impact on the economy. This, together with the environmental and energetic benefits if the renewable generation and use of storage devices, indicate the viability and competitiveness of the system., QC 20181219

Small-scale decentralized polygeneration systems have several energetic, economic and environmental benefits. However, using multiple energy sources and providing multiple energy services can lead to complicated studies which require advanced optimization techniques for determining optimal solutions. Furthermore, several parameters can influence the design and performance of a polygeneration system. In this study, the effects of heat load, renewable generation and storage units on the optimal design and performance of a polygeneration system for a hypothetical hospital located in northern Italy are investigated. The polygeneration system shows higher performance compared to the reference system, which is based on the separate generation of heat and power. It reduces fuel consumption by 14–32%, CO2 emissions by 10–29% and annualized total cost by 7–19%, for various studied scenarios. The avoided fuel and electricity purchase of the polygeneration system has a positive impact on the economy. This, together with the environmental and energetic benefits if the renewable generation and use of storage devices, indicate the viability and competitiveness of the system., QC 20180531

Renewable energy sources contribute to overcome the problem of environmental pollution and secure the energy independency every country needs, while at the same time the autonomous microgrids can improve the electrification rates of poorer countries. In this article, the modeling process and operation of an autonomous hybrid power system are studied for a hypothetical case study of electrification of a remote village of 100 inhabitants in Kenya. The microgrid consists of photovoltaics, wind turbine, batteries, diesel genset, basic loads of different priorities, water pumping and purification load. The system is modeled in Simulink MATLAB and is simulated in terms of power management. The primary load is categorized in different priorities, while water pumping and purification is used as deferrable load. The "load following" dispatch strategy is adopted. The outputs of the model are the power produced by the various sources and the power consumed by all loads during the simulation time, as well as the produced and consumed energy, information on the battery operation and the dumped power or the power shortage. Both the microgrid's operation and the performance of the dispatch strategy are evaluated considering the level on which the citizens' energy needs are covered and the efficient management of the produced energy. Managing the extra power or tackling the deficit of power in the system are the key issues to be addressed. After all, the model represents reliably the behavior of the microgrid and several improving actions are suggested, based on the results analysis.

Renewable energy sources contribute to overcome the problem of environmental pollution and secure the energy independency every country needs, while at the same time the autonomous microgrids can improve the electrification rates of poorer countries. In this article, the modeling process and operation of an autonomous hybrid power system are studied for a hypothetical case study of electrification of a remote village of 100 inhabitants in Kenya. The microgrid consists of photovoltaics, wind turbine, batteries, diesel genset, basic loads of different priorities, water pumping and purification load. The system is modeled in Simulink MATLAB and is simulated in terms of power management. The primary load is categorized in different priorities, while water pumping and purification is used as deferrable load. The "load following" dispatch strategy is adopted. The outputs of the model are the power produced by the various sources and the power consumed by all loads during the simulation time, as well as the produced and consumed energy, information on the battery operation and the dumped power or the power shortage. Both the microgrid's operation and the performance of the dispatch strategy are evaluated considering the level on which the citizens' energy needs are covered and the efficient management of the produced energy. Managing the extra power or tackling the deficit of power in the system are the key issues to be addressed. After all, the model represents reliably the behavior of the microgrid and several improving actions are suggested, based on the results analysis., QC 20180312

With environmental concerns, alternative solutions for generating electricity while decreasing the consumption of fossil fuels have gained a great importance. Polygeneration is one of these solutions which is also capable to increase the technical performance of electricity generation. Polygeneration systems are available in large scale, medium scale and small scale. This study focuses on small scale polygeneration systems specifically for residential applications. Type and size of the components and the system’s operational strategy plays a significant role in polygeneration system design as these factors affect the system cost and also environmental impacts. This study aims to propose a guide for component selection, sizing and addressing a suitable operational strategy for a predefined system configuration. Decision making criteria is defined for component selection by a comprehensive literature review. Internal combustion engines, Stirling engines, micro gas turbines and fuel cells are investigated within these criteria. This provides the user an insight on component selection. When combined with factors such as market conditions, location and especially household demand profile, a selection can easily be made by the customer. For component sizing and operational strategy, a model has been implemented in Matlab. A baseline case model with a predefined system configuration and operational strategy was defined. The baseline case system includes a prime mover, a back-up auxiliary boiler, a vapor compression refrigeration chiller, a thermal energy storage and solar thermal collectors for the domestic hot water demand. The operational strategy is defined as thermal load following. For the case study, this model was altered for different cases with alterations on the operational strategy and the system configuration in order to identify the optimal solution for the user where the total annual cost is minimized while satisfying all kinds of end-use demands of a single

In this paper a small-scale energy system called emergency container is presented. This container has lots of applications and can be designed as stationary solution in remote areas such as rural electrification and a mobile solution for disaster situation, military purposes and exploration teams. In this study the container is a hybrid PV/wind/engine energy system that is designed to provide electricity and drinkable water for 1000 person in disaster situations. A transient model implemented in Transient Simulation System (TRNSYS) program is developed and performance of the system during one-year operation for two locations (Nairobi in Kenya and Nyala in Sudan) with relatively high solar insolation is analyzed. The result of the model is significantly important in order to choose the right size of the different components. Due to the fluctuations of solar and wind energy as well as the importance of the battery life cycle, there is a need to have a smart power management and an appropriate fast response control system. In order to achieve it and to fulfill the energy demand as much as possible through renewable energies, a dispatch strategy is introduced and a control algorithm is applied to the model. This control algorithm has increased system reliability and power availability. The transient simulation shows that the share of power generation by solar energy is 63% and 80% and the share of wind power is 27% and 12% in Nairobi and Nyala respectively. It means that most of the energy demand (around 90%) can be covered by renewable energy. This results in significant mitigation of environmental issues compared to using only diesel engine that is a common solution in disaster situations., QC 20150226

Polygeneration energy systems using multiple energy sources (e.g., wind, biomass, solar) and delivering multiple energy services (i.e., heating, cooling, and electricity) have potential economic and environmental benefits over traditional energy generation systems. However, for maximized benefits, such systems must be the correct size and have a suitable operating strategy implemented. In this study, an optimization model is proposed to identify the optimal design and operating strategy of a complex polygeneration system. The system includes photovoltaic modules, solar thermal units, wind turbines, combined heat and power units, energy storages (hot, cold, and electric), vapor compression and absorption chillers, and a boiler. The interactions between these units are managed based on the integrated operating strategies: following thermal load, following electric load and modified base load. A particle swarm optimization is used as an optimization algorithm and the objective function is defined to minimize the annualized total cost, fuel consumption, and carbon dioxide emissions using a weighting factor method. The careful incorporation of the realistic operation of the CHP is considered in the theoretical model. This includes the effects of the part-load operation and outdoor temperature on the efficiency and power output of the CHP. In addition, the size dependency of the unit cost of the chillers and CHP units over the search space is taken into account. With this approach, the achieved results would be as close to real conditions as possible. Six configuration scenarios are examined for a case study in a residential building complex located in northern Italy. It is concluded that implementation of the optimized polygeneration system has energetic, economic, and environmental conservation benefits in all these scenarios. The annualized cost and fuel consumption of the optimal solutions decreased by 3–19% and 10–37%, respectively, for the various scenarios compared, QC 20180529

Polygeneration energy systems using multiple energy sources (e.g., wind, biomass, solar) and delivering multiple energy services (i.e., heating, cooling, and electricity) have potential economic and environmental benefits over traditional energy generation systems. However, for maximized benefits, such systems must be the correct size and have a suitable operating strategy implemented. In this study, an optimization model is proposed to identify the optimal design and operating strategy of a complex polygeneration system. The system includes photovoltaic modules, solar thermal units, wind turbines, combined heat and power units, energy storages (hot, cold, and electric), vapor compression and absorption chillers, and a boiler. The interactions between these units are managed based on the integrated operating strategies: following thermal load, following electric load and modified base load. A particle swarm optimization is used as an optimization algorithm and the objective function is defined to minimize the annualized total cost, fuel consumption, and carbon dioxide emissions using a weighting factor method. The careful incorporation of the realistic operation of the CHP is considered in the theoretical model. This includes the effects of the part-load operation and outdoor temperature on the efficiency and power output of the CHP. In addition, the size dependency of the unit cost of the chillers and CHP units over the search space is taken into account. With this approach, the achieved results would be as close to real conditions as possible. Six configuration scenarios are examined for a case study in a residential building complex located in northern Italy. It is concluded that implementation of the optimized polygeneration system has energetic, economic, and environmental conservation benefits in all these scenarios. The annualized cost and fuel consumption of the optimal solutions decreased by 3–19% and 10–37%, respectively, for the various scenarios compared, QC 20180529

Polygeneration energy systems using multiple energy sources (e.g., wind, biomass, solar) and delivering multiple energy services (i.e., heating, cooling, and electricity) have potential economic and environmental benefits over traditional energy generation systems. However, for maximized benefits, such systems must be the correct size and have a suitable operating strategy implemented. In this study, an optimization model is proposed to identify the optimal design and operating strategy of a complex polygeneration system. The system includes photovoltaic modules, solar thermal units, wind turbines, combined heat and power units, energy storages (hot, cold, and electric), vapor compression and absorption chillers, and a boiler. The interactions between these units are managed based on the integrated operating strategies: following thermal load, following electric load and modified base load. A particle swarm optimization is used as an optimization algorithm and the objective function is defined to minimize the annualized total cost, fuel consumption, and carbon dioxide emissions using a weighting factor method. The careful incorporation of the realistic operation of the CHP is considered in the theoretical model. This includes the effects of the part-load operation and outdoor temperature on the efficiency and power output of the CHP. In addition, the size dependency of the unit cost of the chillers and CHP units over the search space is taken into account. With this approach, the achieved results would be as close to real conditions as possible. Six configuration scenarios are examined for a case study in a residential building complex located in northern Italy. It is concluded that implementation of the optimized polygeneration system has energetic, economic, and environmental conservation benefits in all these scenarios. The annualized cost and fuel consumption of the optimal solutions decreased by 3–19% and 10–37%, respectively, for the various scenarios compared, QC 20180529

Polygeneration energy systems using multiple energy sources (e.g., wind, biomass, solar) and delivering multiple energy services (i.e., heating, cooling, and electricity) have potential economic and environmental benefits over traditional energy generation systems. However, for maximized benefits, such systems must be the correct size and have a suitable operating strategy implemented. In this study, an optimization model is proposed to identify the optimal design and operating strategy of a complex polygeneration system. The system includes photovoltaic modules, solar thermal units, wind turbines, combined heat and power units, energy storages (hot, cold, and electric), vapor compression and absorption chillers, and a boiler. The interactions between these units are managed based on the integrated operating strategies: following thermal load, following electric load and modified base load. A particle swarm optimization is used as an optimization algorithm and the objective function is defined to minimize the annualized total cost, fuel consumption, and carbon dioxide emissions using a weighting factor method. The careful incorporation of the realistic operation of the CHP is considered in the theoretical model. This includes the effects of the part-load operation and outdoor temperature on the efficiency and power output of the CHP. In addition, the size dependency of the unit cost of the chillers and CHP units over the search space is taken into account. With this approach, the achieved results would be as close to real conditions as possible. Six configuration scenarios are examined for a case study in a residential building complex located in northern Italy. It is concluded that implementation of the optimized polygeneration system has energetic, economic, and environmental conservation benefits in all these scenarios. The annualized cost and fuel consumption of the optimal solutions decreased by 3–19% and 10–37%, respectively, for the various scenarios compared, QC 20180529

Polygeneration energy systems using multiple energy sources (e.g., wind, biomass, solar) and delivering multiple energy services (i.e., heating, cooling, and electricity) have potential economic and environmental benefits over traditional energy generation systems. However, for maximized benefits, such systems must be the correct size and have a suitable operating strategy implemented. In this study, an optimization model is proposed to identify the optimal design and operating strategy of a complex polygeneration system. The system includes photovoltaic modules, solar thermal units, wind turbines, combined heat and power units, energy storages (hot, cold, and electric), vapor compression and absorption chillers, and a boiler. The interactions between these units are managed based on the integrated operating strategies: following thermal load, following electric load and modified base load. A particle swarm optimization is used as an optimization algorithm and the objective function is defined to minimize the annualized total cost, fuel consumption, and carbon dioxide emissions using a weighting factor method. The careful incorporation of the realistic operation of the CHP is considered in the theoretical model. This includes the effects of the part-load operation and outdoor temperature on the efficiency and power output of the CHP. In addition, the size dependency of the unit cost of the chillers and CHP units over the search space is taken into account. With this approach, the achieved results would be as close to real conditions as possible. Six configuration scenarios are examined for a case study in a residential building complex located in northern Italy. It is concluded that implementation of the optimized polygeneration system has energetic, economic, and environmental conservation benefits in all these scenarios. The annualized cost and fuel consumption of the optimal solutions decreased by 3–19% and 10–37%, respectively, for the various scenarios compared, QC 20180529