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Several socioeconomic factors such as industrialization, population growth, evolution of modern technologies, urbanization and other social activities do heavily influence the increase in energy demand. A thorough understanding of the effects of energy demand to power grid is highly essential for effective planning and operation of a power system network in terms of the available generation and transmission line capacities. This paper presents an optimal power flow (OPF) with the aim to determine the exact nodes through which the network capacities can be increased. The problem is formulated as a Direct Current (DC) OPF model, which is a linearized version of an Alternating Current (AC) OPF model. The DC-OPF model was solved as a single period OPF problem. The model was tested in several case studies using the topology of the IEEE test systems, and the computation speeds of the different cases were compared. The results suggested dual variables of the problem’s constraints as an extra tool for the network designer to see where to increase the network capacities.

BackgroundPlantar intrinsic foot muscles (PIFMs) are composed of 10 muscles and play an essential role in achieving functional diversity in the foot. Previous studies have identified that the morphological profiles of PIFMs vary between individuals. The morphological profiles of a muscle theoretically reflect its output potentials: the physiological cross-sectional area (PCSA) of a muscle is proportional to its maximum force generation, and the muscle fiber length (FL) is its shortening velocity. This implies that the PCSA and FL may be useful variables for characterizing the functional diversity of the individual PIFM. The purpose of this study was to examine how individual PIFMs can be classified based on their PCSA and FL.MethodsIn 26 healthy young adult males, the muscle volume and muscle length of seven PIFMs (abductor hallucis, ABDH; abductor digiti minimi, ABDM; adductor hallucis oblique head, ADDH-OH; ADDH transverse head, ADDH-TH; flexor digitorum brevis, FDB; flexor hallucis brevis, FHB; quadratus plantae, QP) were measured using magnetic resonance imaging. The PCSA and FL of each of the seven PIFMs were then estimated by combining the data measured from the participants and those of muscle architectural parameters documented from cadavers in previous studies. A total of 182 data samples (26 participants × 7 muscles) were classified into clusters using k-means cluster analysis. The optimal number of clusters was evaluated using the elbow method.ResultsThe data samples of PIFMs were assigned to four clusters with different morphological profiles: ADDH-OH and FHB, characterised by large PCSA and short FL (high force generation and slow shortening velocity potentials); ABDM and FDB, moderate PCSA and moderate FL (moderate force generation and moderate shortening velocity potentials); QP, moderate PCSA and long FL (moderate force generation and rapid shortening velocity potentials); ADDH-TH, small PCSA and moderate FL (low force generation and moderate shortening velocity potentials). ABDH components were assigned equivalently to the first and second clusters.ConclusionsThe approach adopted in this study may provide a novel perspective for interpreting the PIFMs’ function based on their maximal force generation and shortening velocity potentials.

The electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialisation, population growth, urbanisation and, of course, the evolution of modern technologies in this 4th industrial revolution era. Such a rapid increase in energy demand introduces a huge challenge into the power system, which has paved way for network operators to seek alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such an increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a DC TNEP model that minimises the capital costs of additional transmission lines, network reinforcements, generator operation costs and the costs of renewable energy penetration, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model was tested in several IEEE test systems in multi-period scenarios. We also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variable decomposition techniques. Moreover, we intend to provide additional recommendations in terms of in which particular year (within a 20 year planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. This is achieved by running incremental period simulations from the base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time, even for large power grid system.

This study is a product of the Africa Infrastructure Country Diagnostic (AICD), a project designed to expand the world's knowledge of physical infrastructure in Africa. The AICD provides a baseline against which future improvements in infrastructure services can be measured, making it possible to monitor the results achieved from donor support. It also offers a more solid empirical foundation for prioritizing investments and designing policy reforms in the infrastructure sectors in Africa. The book draws upon a number of background papers that were prepared by World Bank staff and consultants, under the auspices of the AICD. The main findings were synthesized in a flagship report titled Africa's infrastructure: A time for transformation, published in November 2009. Meant for policy makers, that report necessarily focused on the high-level conclusions. It attracted widespread media coverage feeding directly into discussions at the 2009 African union commission heads of state summit on infrastructure.

This report summarizes the results of a recent review of the emerging experience with the design and implementation of policy instruments to promote the development of renewable energy (RE) in a sample of six representative developing countries and transition economies ('developing countries') (World Bank 2010). The review focused mainly on price- and quantity-setting policies, but it also covered fiscal and financial incentives, as well as relevant market facilitation measures. The lessons learned were taken from the rapidly growing literature and reports that analyze and discuss RE policy instruments in the context of different types of power market structures. The analysis considered all types of grid-connected RE options except large hydropower: wind (on-shore and off-shore), solar (photovoltaic and concentrated solar power), small hydropower (SHP) (with capacities below 30 megawatts), biomass, bioelectricity (cogeneration), landfill gas, and geothermal. The six countries selected for the review included Brazil, India, Indonesia, Nicaragua, Sri Lanka, and Turkey.

Information and communication technologies (ICTs) have been a remarkable success in Africa. Across the continent, the availability and quality of service have gone up and the cost has gone down. In just 10 years dating from the end of the 1990s mobile network coverage rose from 16 percent to 90 percent of the urban population; by 2009, rural coverage stood at just under 50 percent of the population. Although the performance of Africa's mobile networks over the past decade has been remarkable, the telecommunications sector in the rest of the world has also evolved rapidly. Many countries now regard broadband Internet as central to their long-term economic development strategies, and many companies realize that the use of ICT is the key to maintaining profitability. This book is about that challenge and others. Chapters two and three describe the recent history of the telecommunications market in Africa; they cover such issues as prices, access, the performance of the networks, and the regulatory reforms that have triggered much of the investment. This part of the book compares network performance across the region and tries to explain why some countries have moved so much more quickly than others in providing affordable telecommunications services. Chapter four explores the financial side of the telecommunications revolution in Africa and details how the massive investments have been financed and which companies have most influenced the sector. Chapter five deals with the future of the sector. The final chapter synthesizes the main chapters of the book and presents policy recommendations intended to drive the sector forward.

This book reviews the major developments in and the lessons learned from the 21-year (1991-2012) experience with private sector participation (PSP) in the power sector in India. It discusses the political economy context of the policy changes, looks at reform initiatives that were implemented for the generation sector, describes transmission and distribution segments at different points in the evolution of the sector, and concludes with a summary of lessons learned and a suggested way forward. The evolution of private participation in the Indian power sector can be divided into different phases. Phase one was launched with the opening of the generation sector to private investment in 1991. Phase two soon followed - early experiments with state-level unbundling and other reform initiatives, including regulatory reform, culminating in divestiture, and privatization in Orissa and Delhi respectively. Phase three, the passage of the electricity act of 2003 by the central government, followed by a large increase in private entry into generation and forays into transmission and experiments with distribution franchise models in urban and rural areas during the 11th five-year plan (2007-12) period. In phase four, at the start of the 12th five-year plan (2012-17), the sector is seeing a sharp reduction in bid euphoria and greater risk aversion on the part of bidders, who are concerned about access to basic inputs such as fuel and land. In this context, the report is structured as follows: chapter one gives introduction; chapter two presents private sector participation in thermal generation; chapter three presents private sector participation in transmission; chapter four deals with private sector participation in distribution; chapter five deals with private sector participation in the Indian solar energy sector; chapter six deals with financing of the power sector; chapter seven presents emerging issues and proposed approaches for the Indian power sector; and chapter eight give updates.

Published forecasts underestimate renewable energy capacity growth and potential cost reductions, creating uncertainty around investment decisions and slowing progress. Scenario-based projections diverge widely, driven by variations in modelling techniques and underlying assumptions, with policy-based models typically being overly conservative. With historical generation capacity and cost data readily available, this research demonstrates that data-driven approaches can be leveraged to improve long-term capacity and cost forecasts of solar, wind, and battery storage technologies. Unlike exponential growth models prevailing over shorter time scales, logistic curves requiring asymptotic limits, or machine learning algorithms dependent on extensive datasets, this analysis demonstrates that temporal quadratic regressions are a better starting point to represent capacity growth trends over two to three decades. When coupled with published learning rates, trend-based capacity forecasts provided tighter and lower capital and levelized cost of energy outlooks than most reviewed scenarios, with photovoltaics global average levelized cost of energy reducing from 0.057/kWh to below USD 0.03/kWh by 2030 and below USD 0.02/kWh by 2040. Greater transparency on manufacturing ecosystems is proposed so that more advanced analytical techniques can be utilized. This analysis indicates that without direct interventions to accelerate the growth in wind power generation, global renewable energy technology deployment will fall short of the generation capacities required to meet climate change objectives.

As the need for energy storage systems (ESSs) capacity is increasing due to high accommodation of renewable resources, it is crucial to analyze in which location and for what purpose the ESSs are required to achieve the highest efficiency. Investors and system operators can place and operate the ESSs as expected based on this analysis. Therefore, this study assesses the specific roles of ESSs in a grid system based on their optimal capacity needs, locations, and operations. A long-term simulation model using mixed-integer programming is proposed to obtain these optimal solutions, such as ESS capacity and operational schedules for energy and reserves. Four-week operational simulations are performed for each month using data from the California Independent System Operator. ESSs are placed at sites with solar photovoltaic (PV) systems or wind farms, at baseload generator buses, and at load buses to verify the role of ESSs, depending on the locational differences. The detailed roles are analyzed from the aspects of flexible capacity supply, reserve deployments, time-shifting renewable and thermal energy generation, and costs. The results show that the ESSs on the baseload generation side provide flexibility by time-shifting baseload generation and turn on baseload generators, even when the net load is small. For instance, the required capacity of the flexible thermal generators, such as natural gas turbine generators, is about 3004 MW without the ESS operations in May. When 450 MW ESSs colocated with solar PVs are operated, the required flexible capacity of the thermal generators is lowered to 2404 MW. Moreover, ESSs are highly utilized as a downward reserve provider, although their costs for reserves are higher than thermal generators.

Shading on photovoltaic (PV) modules due to shadows, covering, dust, etc., usually characterized as semi-transparent, will significantly affect the power generation capacity. No systematic study has considered the impact of semi-transparent coverings on the power generation capacity of PV modules. This paper covers a single cell in the PV module using a covering with a transmittance of 18.55% and systematically investigates its impact on the power generation capacity. The open-circuit voltage (Voc) of the PV module is nearly unaffected by semi-transparent coverings because the covered cell can be considered as working at a lower irradiance and thus can output a voltage close to that of the uncovered cell. The short-circuit current (Isc) is significantly affected by coverings because it is co-contributed by the photocurrent (evaluated based on the covering ratio R and transmittance) and the reverse bias current ΔIsc (the covered cell is in a reverse bias state). The ΔIsc increases with R because more charge accumulates at the bi-ends of the covered cell; but, it decreases at full covering, which implies that in a partially covered case the uncovered part contributes more to ΔIsc than the covered part. The fill factor (FF) of the PV module first increases and then decreases with R, as the equivalent resistance of the covered cell increases rapidly with R, which replaces the wire resistance in dominating the series resistance of the PV module when R > 0.6. This work is of great theoretical significance in analyzing the output characteristics of PV modules under real conditions.