This study discusses the potential of power-to-heat (P2H) as an effective option to reduce greenhouse gas emissions in the energy sector. P2H promotes the integration of renewables into the power grid by allowing otherwise unused electricity from renewable resources to be used for space heating. This effect is measured from a techno-economic perspective. Therefore, a linear problem is defined by minimizing the overall energy costs which is solved by the open source program urbs. The model is verified through a case study regarding the municipality Greifswald in 2015 with dominant wind energy. Results indicate that sector coupling of power and heat leads to further integration of renewables while keeping overall system costs low. Specific energy costs and carbon abatement costs are compared to renovation of the building stock for the years 2030 and 2050. We find that abatement costs for reducing emissions by 80% in 2050 would be 20 times higher through ambitious renovation compared to a moderate renovation combined with P2H in the district heating area with 290 € per t CO₂. Allowing excess renewable energy to be used for decentralized P2H use would further reduce system CO₂ avoidance costs to 97 € per t CO₂.

Lebanon electricity crisis continues to escalate. Rationing hours still apply across the country but with different rates. The capital Beirut is subjected to 3 hours cut while other cities, town, and villages may endure 9 to 14 hours of power shortage. To mitigate this situation, private diesel generators distributed illegally all over the country are being used to bridge the gap in the power supply. Almost every building in large cities has its own generator and individual villages may have more than one generator supplying their loads. These generators together with their private networks form incomplete and ill-designed and managed microgrids (MG) but can be further developed to become renewable energy-based MG operating in the island- or grid-connected modes. This paper will analyze the potential of introducing MG to help resolve the energy crisis in Lebanon. It will investigate the usefulness of developing MG under the prevailing situation of existing private power supply service providers and in light of the developed national energy policy that supports renewable energy development. A case study on a distribution feeder in a rural area will be analyzed using HOMER software to demonstrate the usefulness of introducing photovoltaic (PV) arrays along the existing diesel generators for all the stakeholders. Namely, the developers, the customers, the utility and the community at large. Policy recommendations regarding MG development in Lebanon will be presented on the basis of the accumulated experience in private generation and the privatization and public-private partnership laws.

In the present work, development of a new vertical-axis unidirectional wave rotor is reported. The wave rotor is a key component of a wave energy converter (WEC), which harvests energy from ocean waves. Differing from the huge majority of WEC designs that perform reciprocating motions (heaving up and down, swaying back and forth, etc.), our wave rotor performs unidirectional rotation about a vertical axis when directly exposed in waves. The unidirectional feature of the rotor makes the rotor respond well in a wide range of the wave frequency. The vertical axis arrangement of the rotor makes the rotor insensitive to the wave propagation direction. The rotor employs blades with a cross-section in an airfoil shape and a span curled into a semi-oval shape. Two sets of blades, with one nested inside the other, constitute the rotor. In waves, water particles perform an omnidirectional motion that constantly changes in both spatial and temporal domains. The blade nesting permits a compact rotor configuration that ‘sees’ a relatively uniform local flow in the spatial domain. The rotor was experimentally tested in simulated waves in a wave flume under various conditions. The testing results show a promising unidirectional rotor that is capable of extracting energy from waves at a capture width ratio of 0.08 to 0.15, depending on detailed wave conditions.

Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Countries around the world are demanding renewable energy resources (RES). Among different sources of alternate energy, solar energy is prominent and promising alternatives to meet the future electricity needs. Recently, modified energy regulation in Jordan has allowed the customers to install their own photovoltaics generation (PVs) to cover their full energy consumption. This paper investigates the Harmonics emission from MW scale grid-connected photovoltaics and its impact on the Jordanian distribution networks. The monitored 5 MW PV Plant was connected to the main substation (132/33 kV) via two 33 kV feeders. These two feeders were monitored at the main substation. Several electrical parameters are monitored, namely; voltage, current, harmonics contents, total harmonics distortion (THD), active power, reactive power and power factor. The recorded measurement shows that the current THD reaches 26.2% for one feeder and 38.04% for the second feeder. with dominant harmonics contents in phase in the 5ᵗʰ and 7ᵗʰ orders. The interesting results were observed that the higher THD level occurs when the PV plant injects reactive power into the substation, while under unity power factor the level THD is reduced.

This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

In context of the energy transition in Germany, the importance of so-called virtual power plants in the energy supply continues to increase. The progressive dismantling of the large power plants and the ongoing construction of many new decentralized plants result in great potential for optimization through synergies between the individual plants. These potentials can be exploited by mathematical optimization algorithms to calculate the optimal application planning of decentralized power and heat generators and storage systems. This also includes linear or linear mixed integer optimization. In this paper, procedures for reducing the number of decision variables to be calculated are explained and validated. On the one hand, this includes combining n similar installation types into one aggregated unit. This aggregated unit is described by the same constraints and target function terms as a single plant. This reduces the number of decision variables per time step and the complexity of the problem to be solved by a factor of n. The exact operating mode of the individual plants can then be calculated in a second optimization in such a way that the output of the individual plants corresponds to the calculated output of the aggregated unit. Another way to reduce the number of decision variables in an optimization problem is to reduce the number of time steps to be calculated. This is useful if a high temporal resolution is not necessary for all time steps. For example, the volatility or the forecast quality of environmental parameters may justify a high or low temporal resolution of the optimization. Both approaches are examined for the resulting calculation time as well as for optimality. Several optimization models for virtual power plants (combined heat and power plants, heat storage, power storage, gas turbine) with different numbers of plants are used as a reference for the investigation of both processes with regard to calculation duration and optimality.

The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer's perspective. The aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks, neuro-fuzzy models and others for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

During the last years, the economic and energy crisis has spread throughout the world and has become particularly noticeable in Greece. For this reason, the careful planning of the buildings and the effort to save energy is necessary. Within the broader building sector, Passive House is a standard home that offers high energy efficiency, comfort, economy and environmental friendliness. The Passive Building first appeared in Darmstadt, Germany in 1991 and had since begun to spread. The requirements to qualify a passive building are particularly high. However, the energy savings proposals are many. Interventions in the building's shell, in the electromechanical systems, can easily be done. So, large or small amounts of energy can be saved. In our days, engineers have many choices of software tools that offer great possibilities of simulating reality. In the present dissertation, TEE-KENAK and RETSCREEN software tools are used for the energy upgrading of a building apartment located in the area of Larissa in Greece in order to find the optimal scenario. Various energy saving proposals, such as the replacement of fluorescent lamps with led ones, the upgrade of control systems, the use of solar panels for water heating and the placement of external thermal insulation, are being studied according to the potential of each program and the corresponding conclusions are drawn. The results show that the energy consumption in such a residence in the city of Larissa is reduced a lot but not enough so as to become a zero–energy building. For further research, it is recommended to follow the inverse process, that is, the designing from scratch, a building with the necessary specifications to be passive.

Increased energy consumption in the Academic buildings, creates the need to implement energy saving measures and to take advantage of the renewable energy sources to cover the electrical needs of those buildings. An Academic Library will be used as a case study. With the aid of RETScreen software that takes into account the energy consumptions and characteristics of the Library Building, it is proved that measures such us the replacement of fluorescent lights with led lights, the installation of outdoor shading, the replacement of the openings and Building Management System installation, provide a high level of energy savings. Moreover, given the available space of the building and the climatic data, the installation of a photovoltaic system of 100 KW can also cover a serious amount of the building energy consumption, unlike a wind system that seems uncompromising. Lastly, HOMER software is used to compare the use of a photovoltaic system against a wind system in order to verify the results that came up from the RETScreen software concerning the renewable energy sources.

With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

‘Theagenio’ in Thessaloniki exists and works for three centuries now as a hospital. Since 1975 it has been operating as an Integrated Special Cancer Hospital and since 1985 it has been integrated into the National Health System. ‘Theageneio’ Cancer Hospital is located at the central web of Thessaloniki residential complex and consists of two buildings, the ‘Symeonidio Research Center’, which was completed in 1962 and the Nursing Ward, a project that was later completed in 1975. This paper examines the design of the Hospital Unit according to the requirements of the energy design of buildings. Initially, the energy characteristics of the Hospital are recorded, followed by a detailed presentation of the electromechanical installations. After the existing situation has been captured and with the help of the software TEE-KENAK, different scenarios for the energy upgrading of the buildings have been studied. Proposals for upgrading concern both the shell, e.g. installation of external thermal insulation, replacement of frames, the addition of shading systems, etc. as well as electromechanical installations, e.g. use of ceiling fans, improvements in heating and cooling systems, interventions in lighting, etc. The simulation calculates the future energy status of the buildings and presents the economic benefits of the proposed interventions with reference to the environmental profits that arise.

This paper emphasizes the simulation study performed on a Gorlov helical turbine by altering the revolution index of the helical profile. Gorlov helical turbine is the latest addition on reaction turbines, which are used to generate energy from Perennial/tidal source. The paper follows an effective methodology to investigate the viability of obtaining the optimum output characteristics of a scaled hydrokinetic helical turbine subjected to a cross-flow velocity of 1.5m/s in a rectangular duct of 1 square meter area. Six models of Gorlov Helical turbines with diameter 600 mm and height 600 mm were drafted with a different index of revolution. A significant rise in the output torque of the turbine was not evident with the different index of revolution even as the probability of finding a section at every probable angle of attack is likely to rise with the index of revolution, however, the tip speed was found proportional to the index of revolution. Studies suggest that 0.25 remains as the optimum value for the index of revolution of the helix.

The conventional dehumidification method in air-conditioning system mostly utilizes a cooling coil to remove the moisture in the air via cooling the supply air down below its dew point temperature. During the process, it needs to reheat the supply air to meet set indoor condition that consumes considerable amount of energy and affect the coefficient of performance of the system. If the processes of dehumidification and cooling are separated and operated respectively, the indoor conditions will be more efficiently controlled. Therefore, decoupling the dehumidification and cooling processes in heating, ventilation and air conditioning system is one of the key technologies as membrane dehumidification processes for next generation. The membrane dehumidification method has the advantages of low cost, low energy consumption, etc. It utilizes the pore size and hydrophilicity of the membrane to transfer water vapor by mass transfer effect. The moisture in the supply air is removed by the potential energy and driving force across the membrane. The process can save the latent load used to condense water, which makes more efficient energy use because it does not involve heat transfer effect. In this work, the performance measurements including the permeability and selectivity of water vapor and air with the composite and commercial membranes were conducted. According to measured data, we can choose the suitable dehumidification membrane for designing the flow channel length and components of the planar dehumidifier. The vacuum membrane dehumidification system was setup to examine the effects of temperature, humidity, vacuum pressure, flow rate, coefficient of performance and other parameters on the dehumidification efficiency. The results showed that the commercial Nafion membrane has better water vapor permeability and selectivity. They are suitable for filtration with water vapor and air. Meanwhile, Nafion membrane has a promising potential in dehumidification process.

Urban household cooking fuel choice is highly influenced by human behavior, and energy culture parameters such as cognitive norms, material culture and practices. Although these parameters have a leading role in Kathmandu for cleaner households, they are not incorporated in the city’s energy policy. This paper aims to identify trade-offs to transform resident behavior in cooking pattern towards cleaner technology from the site survey study, observation, and quantitative analysis. The analysis recommends implementing a collaborative cultural model for changing impact on the neighborhood from the policy level. The results show that each household produces 439.56 kg of carbon emission each year and 20 percent uses unclean technology due to low-income level. Residents who use liquefied petroleum gas (LPG) as their cooking fuel have suffered from an energy crisis every year that has created fuel hoarding, which ultimately creates more energy demand and carbon exposure. To improve residents’ energy consumption habits, the result recommends the city using soft power of collaboration of residents, private sectors, and government to change their energy culture and behavior.

Purpose: the current status of examination of Diesel engines running on algal oils is in a state of flux. An extensive and systematic literature search was done showing that over the period of 2000 to 2017, only the oils obtained from three different species of algae, namely Tetraselmis suecica, Botryococcus braunii, and Chlorella protothecoides were evaluated as fuels for compression ignition (CI) engines through the extensive bench tests. Therefore, the development of alternative fuels particularly algae-derived oils needs further investigation. Methodology/approach: an experimental study was conducted on a 1Z-type internal combustion engine (ICE) running on the low load (Pe=60 Nm), average load (Pe=90 Nm) and high load (Pe=120 Nm) modes (n=const.=2000 rev-1) and using Diesel fuel (DF), high purity P. moriformis microalgal oil (PMO) and their 30% and 70% blends (PMO30; PMO70) as fuel. Variation of seven parameters, namely Brake specific fuel consumption (BSFC, g/kWh), Net efficiency (Ne), Exhaust gas temperature (exhT, K), Carbon dioxide (CO2, %), Hydrocarbon (HC, ppm), Nitrogen oxides (NOx, %) and Smoke (m-1) emissions were a target of research on the effect of performance appraisal of the CI engine. The received data for pure DF during engine bench testing at Pe=60; 90; 120 Nm has been assumed as a reference (100%) for the comparison with PMO30, PMO70 and PMO. Accordingly, following results for DF have been obtained: (i) Pe=60 Nm: BSFC (272.119 g/kWh), Ne (0.316), exhT (649 K), CO2 (5.271%), HC (7.443 ppm), NOx (309.429 ppm), Smoke (0.086 m-1); (ii) Pe=90 Nm: BSFC (255.267 g/kWh), Ne (0.344), exhT (724.286 K), CO2 (6.936%), HC (7.329 ppm), NOx (480.571ppm), Smoke (0.098 m-1); and (iii) Pe=120 Nm: BSFC (243.710 g/kWh), Ne (0.357), exhT (779.571 K), CO2 (8.371%), HC (7.214ppm), NOx (629.714 ppm), Smoke (0.107 m-1). Findings: following tendencies have been observed for 1Z-type engine operating on oxygenated fuels in comparison to DF, at Pe=60 Nm: (i) PMO30 (BSFC (+1.03%), Ne (+3.29%), exhT (+1%), CO2 (+2.34%), HC (+6.70%), NOx (+0.35%), Smoke (–17.50%)), (ii) PMO70 (BSFC (+7.50%), Ne (+6.65%), exhT (+2%), CO2 (+5.15%), HC (+17.85%), NOx (+1.15%), Smoke (–26.67%)), (iii) PMO (BSFC (+10.43%), Ne (+12.11%), exhT (+2.29%), CO2 (+6.87%), HC (+22.04%), NOx (+1.26%), Smoke (–28.83%)). For Pe=90 Nm: PMO30 (BSFC (–0.35%), Ne (+2.56%), exhT (+0.83%), CO2 (+1.81%), HC (+6.98%), NOx (+1.31%), Smoke (–25.00%)), (ii) PMO70 (BSFC (+6.58%), Ne (+5.35%), exhT (+1.84%), CO2 (+4.68%), HC (+8.97%), NOx (+1.63%), Smoke (–33.92%)), (iii) PMO (BSFC (+12.37%), Ne (+7.89%), exhT (+2.12%), CO2 (+5.25%), HC (+10.30%), NOx (+1.68%), Smoke (–37.91%)). And for the Pe=120 Nm: (i) PMO30 (BSFC (+2.60%), Ne (+0.65%), exhT (+1.10%), CO2 (+2.30%), HC (+7.13%), NOx (+2.18%), Smoke (–20.27%)), (ii) PMO70 (BSFC (+8.24%), Ne (+4.81%), exhT (+1.39%), CO2 (+3.84%), HC (+9.11%), NOx (+2.72%), Smoke (–37.47%)), (iii) PMO (BSFC (+12.70%), Ne (+8.70%), exhT (+1.64%), CO2 (+5.12%), HC (+14.36%), NOx (+2.90%), Smoke (–41.51%)). Originality/value: this study is a part of larger scale investigation done by authors on numerous synergistic improvements in cultivation of microalgae P. moriformis in humid climate countries as well as on production and appraisal of algal biofuels.

Hydrogen chloride is the most common acid gas emitted by the industries. HCl gas is listed as Title III hazardous air pollutant. It causes severe threat to the human health as well as environment. So, removal of HCl from flue gases is very imperative. In the present study, submerged self-priming venturi scrubber is chosen to remove the HCl gas with water as a scrubbing liquid. Venturi scrubber is the most popular device for the removal of gaseous pollutants. Main mechanism behind the venturi scrubber is the polluted gas stream enters at converging section which accelerated to maximum velocity at throat section. A very interesting thing in case of submerged condition, venturi scrubber is submerged inside the liquid tank and liquid is entered at throat section because of suction created due to large pressure drop generated at the throat section. Maximized throat gas velocity atomizes the entered liquid into number of tiny droplets. Gaseous pollutant HCl is absorbed from gas to liquid droplets inside the venturi scrubber due to interaction between the gas and water. Experiments were conducted at different throat gas velocity, water level and inlet concentration of HCl to enhance the HCl removal efficiency. The effect of throat gas velocity, inlet concentration of HCl, and water level on removal efficiency of venturi scrubber has been evaluated. Present system yielded very high removal efficiency for the scrubbing of HCl gas which is more than 90%. It is also concluded that the removal efficiency of HCl increases with increasing throat gas velocity, inlet HCl concentration, and water level height.

Silver nanoparticles have caught a lot of attention because of its unique physical and chemical properties. Silver nanoparticles embedded in polyvinyl alcohol (PVA/Ag) free-standing film have been prepared by microwave irradiation in few minutes. PVA performed as a reducing agent, stabilizing agents as well as support for silver nanoparticles. UV-Vis spectrometry, scanning transmission electron (SEM) and transmission electron microscopy (TEM) techniques affirmed the reduction of silver ion to silver nanoparticles in the polymer matrix. Effect of irradiation time, the concentration of PVA and concentration of silver precursor on the synthesis of silver nanoparticle has been studied. Particles size of silver nanoparticles decreases with increase in irradiation time. Concentration of silver nanoparticles increases with increase in concentration of silver precursor. Good dispersion of silver nanoparticles in the film has been confirmed by TEM analysis. Particle size of silver nanoparticle has been found to be in the range of 2-10nm. Catalytic property of prepared silver nanoparticles as a heterogeneous catalyst has been studied in the reduction of p-Nitrophenol (a water pollutant) with >98% conversion. From the experimental results, it can be concluded that PVA encapsulated Ag nanoparticles film as a catalyst shows better efficiency and reusability in the reduction of p-Nitrophenol.

This paper presents an energy analysis of a solar assisted trigeneration system using an Ejector for dairy applications. The working fluid in the trigeneration loop is Supercritical CO₂. The trigeneration system is a combination of Brayton cycle and ejector based vapor compression refrigeration cycle. The heating and cooling outputs are used for simultaneous pasteurization and chilling of the milk. The electrical power is used to drive the auxiliary equipment in the dairy plant. A numerical simulation is done with Engineering Equation Solver (EES), and a parametric analysis is performed by varying the operating variables over a meaningful range. The results show that the overall performance index decreases with increase in ambient temperature. For an ejector based system, the compressor work and cooling output are significant output quantities. An increase in total mass flow rate of the refrigerant (primary + secondary) results in an increase in the compressor work and cooling output.

The World Energy Outlook shows that energy markets will substantially change within a few forthcoming decades. First, determined action plans according to COP21 and aim of CO₂ emission reduction have already impact on policies of countries. Secondly, swiftly changed technological developments in the field of renewable energy will be influential upon medium and long-term energy generation and consumption behaviors of countries. Furthermore, share of electricity on global energy consumption is to be expected as high as 40 percent in 2040. Electrical vehicles, heat pumps, new electronical devices and digital improvements will be outstanding technologies and innovations will be the testimony of the market modifications. In order to meet highly increasing electricity demand caused by technologies, countries have to make new investments in the field of electricity production, transmission and distribution. Specifically, electricity generation mix becomes vital for both prevention of CO₂ emission and reduction of power prices. Majority of the research and development investments are made in the field of electricity generation. Hence, the prime source diversity and source planning of electricity generation are crucial for improving the wealth of citizen life. Approaches considering the CO₂ emission and total cost of generation, are necessary but not sufficient to evaluate and construct the product mix. On the other hand, employment and positive contribution to macroeconomic values are important factors that have to be taken into consideration. This study aims to constitute new investments in renewable energies (solar, wind, geothermal, biogas and hydropower) between 2018-2023 under 4 different goals. Therefore, a multi-objective programming model is proposed to optimize the goals of minimizing the CO₂ emission, investment amount and electricity sales price while maximizing the total employment and positive contribution to current deficit. In order to avoid the user preference among the goals, Dinkelbach’s algorithm and Guzel’s approach have been combined. The achievements are discussed with comparison to the current policies. Our study shows that new policies like huge capacity allotment might be discussible although obligation for local production is positive. The improvements in grid infrastructure and re-design support for the biogas and geothermal can be recommended.

The numerical models of the heat exchangers in an ejector refrigeration system (ERS) were developed using a new method and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which was capable of estimating of zones’ length, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS from the point of view of the coefficient of performance (COP) and exergy efficiency (ηII). It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the ηII goes through a maximum before decreasing.

Local generated and distribution system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Enhancement economic and environmental can be achieved when there are interaction and energy exchange between the energy hubs. Network energy system and CO2 optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the grids. The second system uses combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third system is integrated combined heat and power (CHP) system with Organic Rankine Cycle (ORC) system where the thermal waste energy from CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model distributed energy resource system optimization based on energy economics and CO2 emission analyses. The results are compared with the conventional energy system. The results show that CHP system (scenario 2) has annual total cost saving of 21.3% compared to the conventional system and scenario 3 provides annual total cost saving of 32.3%. Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO2 emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.

A new operating point decision method using modified equal area criterion for enhanced transient stability is proposed in this paper. The accelerating and decelerating area was analyzed to calculate power difference between mechanical and electrical power. The proposed operating point of Voltage Source Converter High Voltage Direct Current transmission can enhance the transient stability of its neighborhood generator. Especially, larger critical clearing time and decelerating area was accomplished which means improved transient stability. The proposed method was simulated in single machine infinite bus system and a three-machine infinite bus system in PSS/E environment. Capability of overload and its effect was also discussed and implemented in the system. Also, fast control mode shift for frequency stability control was implemented. The simulation result verifies the validity of the proposed method. Therefore, it will effectively improve angle stability in dynamic analysis.

Some lube oil additives improve the base oil performance such as viscosity index improvers and pour point depressants which are the most important type of additives. In the present work, some homopolymeric additives were prepared by esterification of acrylic acid with different alcohols (1-dodecyl, 1-hexadecyl, and 1-octadecyl )and then homopolymerization of the prepared esters with different ratio of benzoyl peroxide catalyst (0.25%& 0.5 % and 1%). Structure of the prepared esters was confirmed by Infra-Red Spectroscopy. The molecular weights of the prepared homopolymers were determined by using Gel Permeation Chromatograph. The efficiency of the prepared homopolymers as viscosity index improvers and pour point depressants for lube oil was the investigation. It was found that all the prepared homopolymers are effective as viscosity index improvers and pour point depressants.

Production of fuels and chemicals using renewable energy is a promising way for large-scale energy storage and export. Solid oxide electrolysers (SOEs) integrated with renewable source of energy can produce 'Syngas' H₂/CO from H₂O/CO₂ in the desired ratio for further conversion to liquid fuels. As only a waste CO₂ from industrial and power generation processes is utilized in these processes, this approach is CO₂ neutral compared to using fossil fuel feedstock. In addition, the waste heat from industrial processes or heat from solar thermal concentrators can be effectively utilised in SOEs to further reduce the electrical requirements by up to 30% which boosts overall energy efficiency of the process. In this paper, the electrochemical performance of various novel steam/CO₂ reduction electrodes (cathode) would be presented. The efficiency and lifetime degradation data for single cells and a stack would be presented along with the response of cells to variable electrical load input mimicking the intermittent nature of the renewable energy sources. With such optimisation, newly developed electrodes have been tested for 500+ hrs with Faraday efficiency (electricity to fuel conversion efficiency) up to 95%, and thermal efficiency in excess of 70% based upon energy content of the syngas produced.

This paper examines the development of a smart urban corridor straddling the 36 miles long Manchester Ship Canal. Set within the dramatic environs of the historic counties of Cheshire and Lancashire that inspired the mystical landscapes and inception of the first planned industrial estate, the low-lying areas throughout this region are characterized by river settlements and centuries-old agricultural patterns that persist today. The MSC (Manchester Ship Canal) was the inception of the industrial revolution. MSC could provide a contemporary catalyst for the development of a new smart corridor that brings different communities, industries, and government authorities together to support the development of innovative strategies that connect and integrate people, technology and the environment whilst potentiate urban and rural areas sustainable growth. The development of Media City at one end provides a smart typology that could expand across the canal. The proposed distributes Metropole would create smart networks between the distinct; overlapping geographies of the river, farms, villages, business parks, and ports. The proposal would allow these areas to retain their present uses, while becoming part of a larger coordinated smart system of sites, services and ecologies. The goal is to design architecture and infrastructure that support the evolving programmatic smart typologies of the region while mediating the borders between the different industries, cultures, and avocations that are vying to co-exist in the region. Like urban settlements, the rural landscape is artificially shaped to meet social, and economic needs. Like the landscape, urban settlements are shaped by the geographical, topographical, and spatial conditions of the landscapes they occupy. This smart knitted metropole is a Metaphor for the complexity of human habitation and society around Manchester Ship Canal. The paper investigates how urban/rural patterns provide differing conditions for living and working. The project is to read and analyse these urban /rural settlement structures and provide insight into the patterns of living and working that have formed them and possible development of a smart networked corridor that integrate the urban and rural socio-economic and physical infrastructures. Through the application of the Delphi Technique process a series of cross boundaries multidisciplinary meetings and workshops with key experts, partners at City Councils, key developers, industry partners and landowners have been designed to identify consensus potential future scenarios for the MSC. The main paper provides new perspectives and approaches for the development of a smart corridor across the Manchester Ship Canal. Through working cross-disciplinary partnerships the project engaged academics, different local authorities and industry partners to find potential environmental, livability and economic drivers and enablers to establish a set of principles that guide the development of a smart urban corridor for MSC.

A complete fuel cell stack comprises several single cells with end plates, bipolar plates, gaskets and membrane electrode assembly (MEA) components. Electrons generated from cells are conducted through bipolar plates. The amount of cells' components increases as the stack voltage increases, complicating the fuel cell assembly process and mass production. Stack assembly error influence cell performance. PEM fuel cell stack importing laser welding technique could eliminate transverse deformation between bipolar plates to promote stress uniformity of cell components as bipolar plates and MEA. Simultaneously, bipolar plates were melted together using laser welding to decrease interface resistance. A series of experiments as through-plan and in-plan resistance measurement test was conducted to observe the laser welding effect. The result showed that the through-plane resistance with laser welding was a drop of 97.5-97.6% when the contact pressure was about 1MPa to 3 MPa, and the in-plane resistance was not significantly different for laser welding.

This paper explains how to design a regulation loop for a power supply circuit. It also discusses the need of a regulation loop and the improvement of a circuit with regulation loop. A sample design is used to demonstrate how to use PSpice to design feedback loop to control output voltage of a power supply and how to check if the power supply is stable or oscillatory. A sample design is made using a specific Integrated Circuit (IC) available in the PSpice library. A designer can experiment feedback loop design using Cadence Pspice tool. PSpice is easy to use, reliable, and convenient. To test a feedback loop, generally, engineers use trial and error method with the hardware which takes a lot of time and manpower. Moreover, it is expensive because component and Printed Circuit Board (PCB) may go bad. PSpice can be used by designers to test their loop designs without using hardware circuits. A designer can save time, cost, manpower and simulate his/her power supply circuit accurately before making a real hardware using this software package.

Micro Inverters provide Module Embedded Solution for harvesting energy from small-scale solar photovoltaic (PV) panels. In addition to higher modularity & reliability (25 years of life), the MicroInverter has inherent advantages such as avoidance of long DC cables, eliminates module mismatch losses, minimizes partial shading effect, improves safety and flexibility in installations etc. Due to the above-stated benefits, the renewable energy technology with Solar Photovoltaic (PV) Micro Inverter becomes more widespread in Village Nano Grid application ensuring grid independence for rural communities and areas without access to electricity. While the primary objective of this paper is to discuss the problems related to rural electrification, this concept can also be extended to urban installation with grid connectivity. This work presents a comprehensive analysis of the power circuit design, control methodologies and prototyping of 300Wₚ Single Phase PV Micro Inverter. This paper investigates two different topologies for PV Micro Inverters, based on the first hand on Single Stage Flyback/ Forward PV Micro-Inverter configuration and the other hand on the Double stage configuration including DC-DC converter, H bridge DC-AC Inverter. This work covers Power Decoupling techniques to reduce the input filter capacitor size to buffer double line (100 Hz) ripple energy and eliminates the use of electrolytic capacitors. The propagation of the double line oscillation reflected back to PV module will affect the Maximum Power Point Tracking (MPPT) performance. Also, the grid current will be distorted. To mitigate this issue, an independent MPPT control algorithm is developed in this work to reject the propagation of this double line ripple oscillation to PV side to improve the MPPT performance and grid side to improve current quality. Here, the power hardware topology accepts wide input voltage variation and consists of suitably rated MOSFET switches, Galvanically Isolated gate drivers, high-frequency magnetics and Film capacitors with a long lifespan. The digital controller hardware platform inbuilt with the external peripheral interface is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the PV Micro Inverter is written in C language and was developed using code composer studio Integrated Development Environment (IDE). In this work, the prototype hardware for the Single Phase Photovoltaic Micro Inverter with Double stage configuration was developed and the comparative analysis between the above mentioned configurations with experimental results will be presented.

Integration of Distributed Green Renewable Energy Sources in addition with Battery Energy Storage is an inevitable requirement in a Smart Grid Environment. To achieve this, an Intelligent Green Energy Management System (i-GEMS) needs to be incorporated to ensure coordinated operation between supply and load demand based on the hierarchy of Renewable Energy Sources, Battery Energy Storage and Distribution Grid. A Bi-directional Energy harvester is an integral component facilitating Intelligent Green Energy Management System (i-GEMS) and it is required to meet the technical challenges mentioned as follows: (1) Capability for Bi-directional mode of operation (Buck/Boost) (2) Reduction of Circuit Parasitic to suppress Voltage spikes (3) Converter startup problem (4) High frequency magnetics (5) Higher power density (6) Mode transitions issues during battery charging and discharging. This paper is focused to address the above mentioned issues and targeted to design, develop and implement a Bi-directional Energy Harvester with galvanic isolation. In this work, the hardware architecture for Bi-directional Energy Harvester rated 5 kW is developed with Isolated Full Bridge Boost Converter (IFBBC) as well as Dual Active Bridge (DAB) Converter using Modular Power Electronics hardware which is identical for both Solar PV arrays and Battery Energy Storage. In IFBBC converter, the current fed full bridge is enabled and voltage fed full bridge is disabled using Pulse Width Modulated (PWM) for Boost mode and vice-versa for Buck mode. In DAB converter, all the switches are enabled so as to adjust the phase shift angle between primary full bridge and secondary full bridge to decide power flow directions based on boost/buck mode of operation. Here, the control algorithm is developed to ensure the regulation of the common DC link voltage and maximum power extraction from the Renewable Energy Sources (RES) depending on the selected mode (buck/boost). This paper presents Small Signal Analysis and Modelling for both IFBBC and DAB Converter in a systematic approach. The Circuit analysis and Simulation study are conducted using PSIM 9.0 in three scenarios which are - 1.IFBBC with passive clamp, 2. IFBBC with active clamp, 3.DAB converter. In this work, a common hardware prototype for Bi-directional Energy Harvester with 5 kW rating is built for IFBBC and DAB converter configurations. The power circuit is equipped with right choice of MOSFETs, gate drivers with galvanic isolation, filter capacitors, and filter boost inductor. The experiment was conducted for IFBBC converter with passive clamp under boost mode and the prototype confirmed the simulation results showing the measured efficiency as 89.5% at 3.5 kW output power. The digital controller hardware platform is developed using floating point microcontroller TMS320F2806x from Texas instruments. The firmware governing the operation of the Bi-directional Energy harvester is written in C language and was developed using code composer studio. The comprehensive analyses of the power circuit design, Control Strategy for Battery charging/discharging under buck/boost modes, Choice of voltage regulation loop/Maximum Power Point Tracking (MPPT) loop for Solar Photovoltaic (PV) array and comparative performance evaluation using experimental results for the above mentioned three scenarios will be presented.