This study aspires to assess state of the art storage technologies for fi ve different scenarios including an offshore wind farm, an onshore wind farm, an islanded grid, a microgrid in Egypt and a solar power system. The assessment has been based on two main evaluation tools: The Technology Readiness Level and Applicability Indicators. Based on the evaluated results, it was concluded that mechanical storage technologies are suitable for largescalesystems due to their relative high capital cost and power range. Cryogenic Thermal, Molten Salt and Pumped Heat storage systems have achieved a high applicability score in all the case studies which makes them as a promising solution for the near future. Moreover, the development of small scale Pumped Hydro Storage (PHES) and Compressed Air Energy Storage (CAES) systems would be very benefi cial since these energy storage systems are the most well developed and commercialized ones. It is also expected that during the next decade thermal storage technologies will play a signifi cant role in the storage scheme due their favorable power characteristics. Finally, efforts should be focused on the reduction of the cost of hydrogen storage because hydrogen storage technology is a promising solution and might compete with PHES and CAES in the future.
Solar is a particularly promising sustainable energy source in terms of its potential to displace the burning of fossil fuels for heat and power, heating and even cooling, albeit at a cost. The sun load-factor profile has a close and predictable match to the daily varying energy demand for heat and electricity, both thermal and electrical, and thermal storage for periods of low irradiance can be made readily available. In addition, solar thermal technologies can provide a significant fraction of the hot water demand in households, as well as space heating and cooling in residential buildings and for industrial facilities. In fact, solar heating has been proposed as one of the leading solutions in terms of its potential for greenhouse gas abatement . At the small scale, photovoltaic systems presently dominate the domestic solar market with solar to electrical conversion efficiencies of around 15% and at a competitive cost for the building owner. Solar photovoltaic installations were encouraged in Europe at the local level with financial support and now constitute a large and mature market with continuously falling prices. Solar thermal systems are able to make use of a larger proportion of the solar resource as they convert solar energy into heat with a higher efficiency than the PV conversion efficiency. Moreover, the low temperature heat may be used to satisfying the largest portion of the demand for thermal energy that is currently met by fossil fuels. The development of the solar thermal market is strongly dependent on the availability of the local irradiance level and on the cost of the alternative sources of thermal energy. In some countries in Europe the solar thermal market is quite mature (e.g. Austria), whilst in others, such as in the UK, solar thermal energy still contributes marginally to the energy mix and solar thermal systems are not yet cost competitive. Due to the high costs of solar thermal energysystems, these constitute a relatively small market at present with the potential to grow substantially in the near future.
Microcombinedheat and power (µ-CHP) is one of the low carbon micro-generation technologies which could be installed in buildings in very large numbers and so could play a important part in the operation of any future HDPS. The technologies underpinning µ-CHP include Stirling engines (SE), fuel cells and internal combustion engines (ICE). While fuel cell µ-CHP is still an embryonic technology, the development of engine-based systems has progressed rapidly in recent years. Dentice d’Accadia et al  identified 12 different units at various stages of commercialisation, with sizes ranging from 1-15 kW of electrical output and 3-39 kW of thermal output. Both Honda and SenerTec  are marketing residential-scale ICE µ-CHP devices. Despite the proliferation of the technology and its entry into the market place, it is by no means certain that the installation of a µ-CHP unit within a building will result in significant emissions savings. Several recent studies have addressed this issue [4,5 & 6] indicating that achieving tangible carbon savings with µ-CHP is dependent upon many factors including the operation and control of the unit, the prevailing climate, the behaviour of the building occupants and the magnitude of the heat and power demands. Indeed the studies by Peacock and Newborough  and Kelly and Cockroft  indicated that under certain circumstances CO 2 emissions may increase with the
Climate change and continuously increasing energy prices have driven the need for low carbon and renewable energytechnologies from different sectors, including the domestic sector, by installing higher energy efficiency technologies. One of these technologies is the Stirling engine based micro-combinedheat and power (CHP) which has the potential to achieve lower overall carbon emissions by generating both heat and electricity locally. Its successful implementation to meet the energy demands (thermal and electrical) throughout the year depends on several factors such as the size and type of building and demand profiles. In addition, the deployment of large number of micro-CHPs may have significant impact on the performance of the power distribution networks.
The use of combinedheat and power (CHP) devices (such as gas engines (GE) and gas turbines (GT)), also known as cogeneration, has been growing rapidly in response to efforts to save energy and prevent global warming . CHP can simultaneously generate both electricity and heat from a single fuel source like natural gas, oil, or liquefied propane. Total energy efficiency of CHP reaches 70–85%. Moreover, it is estimated that CHP can potentially reduce primary energy consumption by 40% and CO 2 emissions by 30%, compared
Combinedheat and powertechnologies have various advantages over conventional power generating systems. One of the primary benefits is the more efficient delivery of energy in the form of thermal and electric energy. This is largely due to the recovery of heat that is usually not utilized in conventional energy generating systems, but which makes up for 40 to 70 percent of the heat input into those systems. Cogeneration recovers this thermal energy for useful applications like process heat (in industry) or heating (buildings), thus increasing the overall efficiency of a system to 80 percent or higher. The heat can also be used for cooling using absorption cooling systems. Combinedheat and powertechnologies are mostly realized as relatively small power units of typically less than 50 MW near or on the respective energy user’s property, which is also referred to as distributed generation. However, larger systems may be found in industry and district heating systems. Micro-turbines (< 50kW) can also be used in cogeneration applications. Transmission and distribution benefits can be obtained due to more reliable and flexible distribution and less expensive T&D systems as the energy users are generally located near the cogeneration plant.
the predicted value. There will be losses in the actual voltage of a fuel cell due to: activation losses, pressure and gas concentrations, and ohmic losses. Activation losses are determined by how ions are discharged to and from the electrodes. When the electrons are released and the charged fuel ion combines with the electrolyte ion to form a product, energy is required for this process, which means there will be a voltage drop. The voltage drop may be found from experimental work conducted by Tafel in 1905, where he studied the overvoltage at the surface of an electrode, the results of his work produced the equation known as the Tafel equation:
and numerous algorithms have been proposed for solving this highly nonconvex problem [40, 106, 112], including linear programming, Newton Raphson, quadratic programming, nonlinear programming, Lagrange relaxation, interior point methods, artificial intelligence, artificial neural network, fuzzy logic, genetic algorithm, evolutionary programming and particle swarm optimization [72, 73, 74, 83]. A good number of these methods are based on the Karush-Kuhn-Tucker (KKT) necessary conditions, which can only guarantee a locally optimal solution, in light of the nonconvexity of the OPF problem . This nonconvexity is partially due to the nonlinearity of physical quantities such as active power, reactive power and voltage magnitude. In the past decade, much attention has been paid to devising efficient algorithms with guaranteed performance for the OPF problem. For instance, the recent papers  and  propose nonlinear interior-point algorithms for an equivalent current injection model of the problem. An improved implementation of the automatic differentiation technique for the OPF problem is studied in the recent work . In an effort to convexify the OPF problem, it is shown in  that the load flow problem of a radial distribution system can be modeled as a convex optimization problem in the form of a conic program. Nonetheless, the results fail to hold for a meshed network, due to the presence of arctangent equality constraints . Nonconvexity appears in more sophisticated power problems such as the stability constrained OPF problem where the stability at the operating point is an extra constraint [29, 17] or the dynamic OPF problem where the dynamics of the generators are also taken into account [117, 116]. The recent paper  also proposes a convex relaxation to solve the OPF problem efficiently and tests its results on IEEE systems. Some of the results derived in the present work are related to this well-known convex relaxation. However,  drops the rank constraint of the original OPF without any justification in order to obtain the SDP formulation. We have derived the conditions under which the SDP relaxation is exact.
Solar energy is the most permanent and abundant renewable energy on the earth. However, 80% of the present energy in worldwide is from non-renewable energy like fossil fuels and nuclear energy. These kinds of energy are decreasing gradually and causing the envirnmental problems like pollution. To address this problem, renewable energy, which has significantly lower envirnmental impact, becomes popular not only at the technical level but also at the political level. For example, the Europe Union has a policy to replace 20% of energy consumption with 2020 [1, 2]. Figure 1.1 shows an estimate of the energy demand and resource, breakdown in the future to the years 2050 and 2100 . As shown in this analysis, non-renewable energy will be less that 15% of the total energy, while solar energy will generate 70% of the total power. Among the ways to capture solar energy, photovoltaic cells can be used to directly convert solar energy to electrical energy, which is a more effective way to collect solar energy than indirect conversion like solar heat. Figure 1.2 shows the potential of photovoltaic power in the world and Korea .
DG/CHP can increase reliability and resource adequacy for the power grid as a whole, not just for the facility operator. Rapid growth in local power demand can create localized shortages of power and impactpower quality and reliability of the grid. Considerable concern emerged about the concentration of data centers in the Silicon Valley area of California during the power and fuel crises of 2001. The problems led to local concerns of pollution from overuse of diesel generators and to migration of new and some existing data centers out of the region in search of more reliable power supplies. Based on the ability of utilities to expand supply, transmission, and substation capacity, it could take several years before such shortages are eliminated. DG/CHP can reduce or delay infrastructure investments, making the grid more reliable for all customers.
B22 Under section 4 of the Act, before installing a furnace (except a domestic furnace) in a building or fixed boiler, the local authority must be informed; any such furnace must be capable of being operated continuously without emitting smoke when burning fuel of a type for which the furnace was designed. There is no definition of “furnace”, but a practical interpretation of this word whenever it appears in clean air legislation is usually taken as “any enclosed or partly enclosed space in which liquid, solid or gaseous matter is burned, or in which heat is produced”. Domestic furnaces are defined as those with a maximum heating capacity of 16.12 kilowatts.
The design of a feasible CombinedHeat and Power plant for a small community is presented. Of the many alternatives solid-waste disposal methods available, incineration of solid waste is recommended due to its potential energy recovery of the heat released during solid waste incineration and recovery of valuable by-products that can either be reused, re- cycled or marketed, among other advantages. Hence, an attempt is made to use the heatenergy released during incin- eration of solid waste to produce steam in a boiler, which in turn powers a turbine for eventual generation of electricity. The two processes involved in the generation of electricity for in-plant use or for a small community via a steam tur- bine-generator combination and a gas compressor-gas turbine-generator are presented. The analysis of the amount of energy produced from the solid waste energy-conversion system using an incinerator-boiler-steam turbine-electric gen- erator combination with a capacity of 4.5 tons/day is also presented. The net electric power for a small community was found to be 148.24 kW with an overall efficiency of about 21% having taken cognisance of the process power needs and unaccounted process heat losses. Moreover, exergy analysis of the proposed CHP plant was carried out whereby the respective energy and exergy efficiencies of 83.2% and 62.1% were obtained.
Intermittent renewable energy sources such as wind, solar, run-of-river hydro, tidal streams and wave fluxes present interesting challenges when exploited in the production of electricity, which is then integrated into existing and future grids. We focus on wind energysystems because they have an emerging presence, with new installed capacity approaching 8 GW annually. We survey many studies and compile estimates of regulation, load following and unit commitment impacts on utility generating assets with increasing wind penetration. Reliability (system reserve), observed capacity factors and the effective capacity (ability to displace existing generation assets) of wind energysystems are discussed. A simple energy balance model and some results from utility-scale simulations illustrate the existence of a law of diminishing returns with respect to increasing wind penetration when measured by wind’s
Very recent approaches like Zhao et al. (2017); Plummer et al. (2017) target open-vocabulary for scene parsing and visual relationship detection, respectively. In Plummer et al. (2017), the related work closest to ours, the authors learn a CCA model on top of different combinations of the subject, object and union regions and train a Rank SVM. They how- ever consider each relationship triplet as a class and learn it as a whole entity, thus cannot scale to our setting. Our ap- proach embeds the three components of a relationship sep- arately to the independent semantic spaces for object and relation, but implicitly learns connections between them via visual feature fusion and semantic meaning preservation in the embedding space.
The market for lithium ion batteries continues to grow due to their excellent energy and power densities, which makes them lighter and more compact than any other commercial battery technology. They are also capable of full discharge/charge cycles without reducing the battery’s cycle life, unlike lead acid batteries. They will also typically last about twice as long as lead acid batteries, when operated under optimal conditions. However, the lithium ion batteries currently cost two to three times more than lead acid batteries on a power capacity basis. These
The past few decades have been marked by a rapidly growing mobile cellular communication industry, globally. Presently, according to reports, the number of mobile telephony and wireless network service subscriptions are estimated to be more than four billion people worldwide. This in turn has led to the deployment and proliferation of Base Stations (BSs) transceivers everywhere, to serve mobile network subscribers. These BSs consume a lot of power due to large traﬃc volume of calls and data packets transmission in the cellular networks. According to a report in , it is predicted that by year 2020, telecommunication infrastructure and mobile networks alone would account for approximately 25% of CO2 gas emissions from the ICT sector. Evidently, high power consumption and operational energy eﬃciency cost problems in the mobile networks and their BS infrastructure are becoming major problems for the governments, telecom industries, and scientiﬁc research communities at large. This situation explains, in a way, why ideas like “green radio communications concept” have arisen in recent time, as clearly seen in [2–5]. The use of massive multiple input multiple output (Ma-MIMO) systems, virtual MIMO systems, white spaces and adaptive resource management techniques are some of the envisioned ways to signiﬁcantly reduce energy consumption in mobile cellular networks in literature.
Previous sections have explained the methodology employed in obtaining, analysing and organising into data files the component material related machining information, i.e. recommended tool materials and associated cutting speed parameters, etc. Attention is now focused upon the IMPS algorithm which utilises the data held in the machining files to identify the tool grades appropriate to the component material being machined, generates the associated cutting parameters calculating basic machining times, tool change frequency, etc., and finally ascertains by means of inspecting the Company Standard Tooling Catalogue via the ARCLASS system whether suitable tooling is already a standard item within the Company. The detail of the file layouts referred to hereafter are depicted in Figures 35 and 36. It will be noted that the file named 'Machlnabillty Group 4' is an extended version of Figure 33, the additional data held relating to the hardness speed modification referred to in Section 6.3, details of the specific force constant (or k g value) which facilitates the calculation of power required to remove a volume of
Energy management is gaining increasing attention among industry leaders who recognise the strategic potential of energy efficiency as a means to cost-effectively save energy, reduce GHG emissions and enhance energy security. Systematic energy management is indeed one of the most effective approaches to continuously improve energy efficiency in industries because it equips companies with practices and procedures to identify and implement new opportunities for improvement, and achieve energy-saving objectives on an ongoing basis. When compared to selective measures (ad hoc energy management), continuous application of this process clearly reduces the energy-related costs of a company, as shown in figure 1 below.