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A severe energy crisis has plagued Yemen for decades, and most of the population lack access to electricity. This has harmed the country’s economic, social, and industrial growth. Yemen generates electricity mainly from fossil fuels, despite having a high potential for renewable energy. Unfortunately, the situation has recently been compounded by the country’s continuing war, which has been ongoing since early 2015. It has impacted the country’s energy infrastructure negatively, resulting in power outages. Therefore, this paper aims to provide an updated perspective on Yemen’s current energy crisis and explain its key issues and potential solutions. Besides, it examines the potential, development, and current state of renewable energy sources, such as solar, wind, geothermal, and biomass. Based on the findings, Yemen is one of the world’s wealthiest countries in terms of sunlight and wind speed, and these two resources are abundant in all regions of the country. In addition, this paper sheds light on the solar energy revolution that has arisen since the war started due to the complete outage of the national electricity. Within a few years, solar energy in Yemen has increased its capacity by 50 times and has recently become the primary source of electricity for most Yemenis. Furthermore, the paper discusses the difficulties and challenges that face the implementation of renewable energy investment projects. Numerous recommendations for potential improvements in Yemen’s widespread use of renewable energy are also provided in this paper. All of the ideas presented in this paper are hoped to increase the efforts to grow renewable energy production in Yemen, thereby solving the issues of energy poverty and reducing environmental effects. The presented analysis can be used as a scientific reference for researchers and industrial companies looking for suitable solutions to advance Yemen’s renewable energy.

Multilevel inverters (MLIs) have drawn tremendous attention in the power sector. Application of MLI has grown extensively to improve the power quality and efficiency of the photovoltaic (PV) system. For an MLI interfacing PV system, the size, cost and voltage stress are the key constraints of the MLI that need to be minimized. This paper presents a novel reduced part count MLI interfacing single-stage grid-tied PV system along with a closed-loop control strategy. The proposed MLI consists of n repeating units and a level boosting circuit (LBC) that assists in generating 4n + 7 voltage levels instead of 2n + 3 levels. Three different algorithms are proposed for a proper selection of dc-link voltages to enhance the levels further. A comparative analysis is carried out to confirm the superiority of the developed MLI. The workability of the proposed MLI is investigated with a 1.3 kW PV system. The closed-loop control strategy ensures the maximum power tracking, dc-link voltage balancing, satisfactory operation of the MLI and injection of clean sinusoidal grid current under any dynamic changes. Comprehensive simulation analysis is carried out considering a 15-level MLI structure. Experimental tests further confirm the practicality of the topological advancement for a PV system under different dynamic conditions.

Energy storage systems are bound to play a critical role in the transition towards a decarbonized power sector with high shares of variable renewables. However, an open question is whether all storage capacity that is needed will be profitable under the current market paradigm. In this paper, we assess how the profitability of energy storage systems is affected by the increasing penetration of variable renewables. Moreover, we discuss the potentially detrimental effects of strategic storage capacity withholding on system costs, renewable penetration and the profitability of all technologies.

China has proposed the ambitious 2060 carbon-neutral goal to alleviate environmental deterioration. The deep decarbonization in the power sector is always the focus of attention. However, there are scientific gaps on how this change can be realized, especially in the context of China. The main objective of this paper is to explore the carbon-neutral transition pathways in the Sichuan power sector and determine the capacity requirement of storage measures under different pathways. The EnergyPLAN tool simulates the current and future Sichuan power sector in 2060, including four renewable scenarios. It is found that, all the renewable scenarios can achieve the goal of carbon-neutral in 2060 and their system costs are similar to the reference scenario. Their performance in biomass consumption and electricity exportation differs by pathway. With the introduction of the pumped storage power station, the largest storage capacity of 1229 GWh appears in the high renewable penetration scenario, with a system cost growth of 9.3%. In brief, the methodological steps and results proposed in this paper can be helpful to realize the future decarbonization in the power sector in China.

Wind generation in India is an up-rising power sector in recent times, which is nearly 10% of its total installed generation capacity. India is also exploring the potential of offshore wind energy near the coastal area of Gujarat. This paper presents an optimal and economic methodology to connect wind turbines (WTs) of 1 GW offshore wind farm (OWF) to be constructed near the Gujarat coast. The OWF consists of 500 WTs, with each having capacity of 2 MW. A segment of the proposed layout (about 25% of the total capacity) of the OWF has been identified for this study. Sweep algorithm is used to determine an appropriate number of WT clusters, followed by optimal cabling by minimizing the length of submarine cables of each WT cluster using Clarke and Wright saving algorithm. Each WT cluster is connected to an offshore substation (OS). The optimal placement of OS for the segment of OWF has been determined considering the lowest capital cost for the submarine cable in this study.

Electric Vehicles (EV) are coming with a stupendous load demand that raises enough concerns for the power sector. The backlash of such increased demand is notable at the distribution side with different aspects of EV usage. During winter, EV users favor preconditioning their vehicles before leaving their houses, such as heating the cabin and battery compartment to make the operation of EVs more comfortable. Consequently, such behavior along with a higher penetration of level 2 smart chargers prompt the presence of a new peak in the residential load profile. This new unexpected peak that operators have to face can disturb the performance of the network. To forsee the impact of preconditioning, we simulate multiple scenarios to assess the network’s quality metrics (voltage level and power losses). We expose that preconditioning poses risks on the network in its current state. Furthermore, we evaluate the competencies of network reconfiguration to handle the new imposed preconditioning demand. We find out that reconfiguration will be able to aid the performance of the network to an average EV penetration rate.

The current harmonics of a local low-voltage (LV) power network with two vehicle-to-grid (V2G) chargers connected are evaluated in this paper. Two indicators, the Total Harmonic Distortion (THD) and the Total Demand Distortion (TDD), are calculated based on the monitored data collected from the demonstration site. The system states are grouped into several scenarios according to different charger operational modes, including grid-to-vehicle (G2V), V2G, and off modes. The statistical analysis of the two indicators over a six-month period shows that, in terms of TDD, grid harmonics generally complied with the international standards under all scenarios. The experiments of this demonstration project prove that V2G chargers slightly improve the grid harmonics, which is useful information for charger manufacturers, site and utilities operators, and other power sector stakeholders.

Government of India (GoI) begun an unprecedented lockdown on 25 March 2020 to fight against the COVID-19. The national lockdown has been extended till 31May 2020. The Ministry of Home Affairs (MHA) on 24 March 2020 issued an order detailing the restrictions imposed on the movement of individuals as well as economic activities other than essential services. Nonetheless, the Indian Power Sector also is not invulnerable to this pandemic. The adverse effects already becoming evident in the power sector, however, Nine-Minute Call gained more attention to the media houses. In this article the impact of this pandemic on the Indian Power Sector is discussed to mitigate the long term effect and this study may help to prepare in this type of situation in the future.

A country's economic growth is largely dependent on the stability of its energy sector. The growth of Kenya's power sector is greatly supported by Vision 2030 development blueprint, which is geared at transforming the country into a “middle-income country that is able to provide a high quality of life to all of its citizens by the year 2030”. Though major investments have so far been made in the generation and transmission of power, the distribution sub-sector is yet to reap the full benefits due to a number of challenges ranging from financial to operation and maintenance. Transformers are key components of any power distribution network and despite their specified long operational life, they often fail within a short period of commissioning due to various reasons including vandalism. This has led to great losses to the power distribution sub-sector and consumers alike. This paper proposes an anti-theft system that uses machine learning technique to monitor the pylon's environs against vandals. Results of the study reveals that the system is capable of detecting human images with confidence levels between 68% and 97%.

Large scale Electric Vehicles (EV) penetration is coming with a stupendous energy demand that raises much concerns in the power sector. The impact of this demand is mostly notable at the distribution side as an outcome of EV users home charging preferences. Currently, most EVs charge their batteries through level 1 charger at home. However, the shorter charging times and the declining prices of level 2 chargers favor a switch from level 1 into level 2 chargers at residential premises. As a ramification, this will cause a lamentable peak in the residential load profile, and consequently power utilities will face the impact of elevated number of level 2 chargers with uncontrolled EV charging. To foresee these consequences, using the IEEE-33 Bus radial distribution system, we build a discrete event simulator and present real-life assessment of different EV penetration rates with various level 2 charger adoption rates. We expose that 50% EV penetration along with 50% level 2 chargers deployment may create an undesirable situation on the distribution network. Furthermore, we simulate EV users’ charging behavior over different pricing techniques. The collected results show that available pricing techniques cannot maintain the voltage level over minimum desired threshold especially during peak times.

The reliability of the power stations is main factor in the power sector field in order to understand the performance of the system. It gives the measure of how much power supplied to the customers without any failure.The pollutants which are came from the thermal power plants for the year 2018 was calculated. Reliability is impotant in Generation Expansion Planning. The datas are collected for this study based on the progress report of 2018 which was issued by Southern Regional Committee. This study is considered as Tamil Nadu State power supply system in India. For Environment aspect, the pollutions emitted by thermal plants of Tamil Nadu power sector and reliability indices like Expected Energy Not Served (EENS) for the year 2018 is calculated by the LEAP software (Long Range Energy Alternative Planning).

Over the years, many countries have faced huge financial deficits due to Non-Technical Loss (NTL) in power sector. There are many ways of attempting to illegal use of electricity like by-passing and reversing meters. There have been many attempts to bring down NTL using manual and automated techniques. Manual NTL detection is not proving fruitful as it incurs heavy costs and has a low hit ratio. Due to the shortcoming of manual NTL detection, automated detection of NTL using machine learning classifiers is gaining attention in the research community. The datasets containing NTL belong to the class imbalance domain where regular consumers (negative class) out weight the representation of irregular consumers (positive class). To identify the right number of representative records, many techniques are proposed but selecting the right features in deciding NTL is equally an important task where not much has been contributed to the literature. In this paper, we propose the Incremental Feature Selection (IFS) algorithm which first uses feature importance to identify the most relevant features for NTL detection and then these features are used to test three classifiers namely CatBoost, Decision Tree (DT) Classifier and K-Nearest Neighbors (KNN) for NTL detection. This way, we have not only identified the most relevant features for NTL detection in a real dataset but also have brought down the overall computation time of the classifiers. Moreover, our proposed framework is tested on three performance evaluation metrics used in imbalance domain. The results show that using the most relevant features identified by the IFS algorithm, the three classifiers have the same or slightly better efficiency as compared to using all features.

With the increase in electricity usage through developing countries, the financial crises has enveloped due to energy poverty. Issues such as circular debt are now a major factor that has a drastic impact on the economic condition of such countries. Power sector, being a major constituent of the economic structure of such countries, has a major role to play for changes in economic condition. This paper numerically evaluates the financial challenges in power sector and the inevitable shortcomings in policies with growing circular debt. The case study has been performed on Pakistan and solutions are proposed to mitigate this financial debt with comparative analysis of increasing share of renewables and inexpensive energy in electricity market.

У статті розглянуто сучасні тенденції розвитку відновлюваної енергетики. Попри динамічний розвиток відновлюваної енергетики у світі, світовий енергетичний ринок продовжує базуватися на невідновлюваних енергетичних ресурсах. У статті розглядаються фактори, що впливають на будівництво генеруючих потужностей відновлюваної енергетики. Аналіз засвідчив, що основними рушійними силами розвитку світового сектору відновлюваної енергетики є політичні фактори, зокрема впровадження економічних механізмів, спрямованих на стимулювання генерації електроенергії з відновлюваних енергетичних ресурсів. Такі механізми в основному були впроваджені в електроенергетичному секторі, як наслідок на сьогодні він утримує провідні позиції щодо розвитку відновлюваної енергетики. Водночас недостатня реалізація мотиваційних механізмів у секторах транспорту, опалення та охолодження уповільнила залучення відновлюваних енергетичних ресурсів. Крім того, у статті окреслено основні виклики, які стримують підвищення конкурентоспроможності відновлюваної енергетики на світовому енергетичному ринку. В статье рассмотрены современные тенденции развития возобновляемой энергетики. Несмотря на динамичное развитие возобновляемой энергетики в мире, мировой энергетический рынок продолжает базироваться на невозобновляемых энергетических ресурсах. В статье рассматриваются факторы, влияющие на строительство генерирующих мощностей возобновляемой энергетики. Анализ показал, что основными движущими силами развития мирового сектора возобновляемой энергетики являются политические факторы, в частности внедрение экономических механизмов, направленных на стимулирование производства электроэнергии из возобновляемых энергетических ресурсов. Такие механизмы в основном были внедрены в электроэнергетическом секторе, как следствие сегодня он удерживает ведущие позиции по развитию возобновляемой энергетики. В то же время недостаточная реализация мотивационных механизмов в секторах транспорта, отопления и охлаждения замедлила привлечения возобновляемых энергетических ресурсов. Кроме того, в статье обозначены основные вызовы, которые сдерживают повышение конкурентоспособности возобновляемой энергетики на мировом энергетическом рынке. The paper deals with modern trends in global renewable energy development. Despite the fact that nowadays the dynamic deployment of renewable energy capacities is observed around the world, global energy market continues to be based on non-renewable energy resources. In the paper the drivers for global renewable energy market development and their impact on renewable energy plants construction are examined. The analysis has shown that the main driving forces for world renewable energy sector growth are policy factors, especially implementation of well-designed support mechanisms to promote energy production from renewables. As such support tools were mainly implemented in power sector, now it holds leading position, while insufficient implementation of motivational tools in transport, heating and cooling sectors slowed down their development. In addition, the main challenges, which inhibit increasing the competitiveness of renewable energy on the global energy market, are outlined. The paper has been supported by the Ministry of Education and Science of Ukraine under the projects “System model of efficiency management and forecasting of electricity use” (No. 0118U003583) and “Innovative management of energy-efficient and resource-saving technologies in Ukraine” (No. 0118U003571).

The accuracy of load demand forecasting plays a vital role in economic operation and planning in the power sector. Therefore, many techniques and approaches have been proposed in the literature for forecasting. However, there is still an essential need to develop more accurate load forecast method. In this paper, three different strategies of Multi-Step-Ahead Load Forecasting (MSALF), i.e. Direct Strategy (DS), Recursive Strategy (RS) and DirRec Strategy (Direct-Recursive Strategy or DRS) have been used for electricity load demand forecasting by using the Artificial Neural Network (ANN) with Levenberg-Marquardt (LM) training algorithm. The performance evaluation for three different strategies of MSALF has been analysed on two different substations of NE-ISO data sets. Each data sets is analysed for four different cases. The performance of the DRS is better than DS and RS.

Power Transformer being essential and costlier equipment in the power sector, maintaining its healthiness is a crucial task. Condition monitoring of transformers can help in predicting the kinds of fault and prevent the mishap. It can be achieved through Dissolved Gas Analysis. But interpretation of DGA to find the nature of fault that has occurred within transformer is a difficult job. There are many conventional methods like key gas method, Rogers ratio method, Duval triangle etc. These methods may not provide accurate and precise results in desired time. Therefore, modern heuristic methods can be helpful in reducing the computation time. One on such heuristic method is Artificial Bee Colony algorithm. The results of this method are validated by comparing with the Fuzzy Inference System method on the basis of accuracy, precision, specificity and sensitivity.

This paper aims to propose a framework for accessing relative efficiencies of utilities in power sector dealing in rural distribution in India. Despite of numerous initiatives taken to achieve 100% rural electrification by government of India (GoI), 17% rural households remain unelectrified because distribution companies (DISCOMs) perform sub-optimally. Suggesting non-parametric approach of performance evaluation as a remedy to this shortcoming, the current study engages Data Envelopment Analysis (DEA) technique to perform productivity analysis on 27 DISCOMs. The results showed separate benchmarks for different utilities, as their respective efficiency scores were indicated ranging from 0 to 1, 1 being most efficient. The paper discusses policy recommendations in context with results and their inferences.

The world's electricity demand is ever increasing since the digitalization and industrialization have begun. Bangladesh as a developing country has a power sector that has been one of the fastest-growing ones in South-Asia. A relentless development of its economy is urging the government to increase the generation capacity every year. Bangladesh Power Development Board's master plan aims to generate 39,000 MW by 2030. This study is a representation of the 2030 generation scenarios in terms of real power flows between the 9 electrical zones of Bangladesh. An optimal power flow model with minimum-cost generations is developed in MATPOWER simulation environment. The DCOPF model simulated here, considers a loss-less network where only real power flows among 13 interconnections for the 9 zones are considered. The power flow values and directions obtained here give an approximate idea of the future generation and transmission of real power in Bangladesh for the year 2030.

Residential Sector is among the major consumers of energy especially considering the power sector. The constantly growing energy demand of this sector can be achieved under two scenarios. Either we have to increase the resource supply, or we start producing comparatively more efficient devices. This study assesses the energy savings obtained through technological advancements in residential sector of Pakistan through utilization of Solar Fans. Long Range Energy Alternative Planning (LEAP) model is used to forecast the energy outlook of this sector in 2040 under different scenarios. A complete feasibility study has been performed depicting both the energy savings and economic considerations. Results obtained from the model depicts that Solar fans can attain a penetration level of 30% by 2040. This will consequently result in energy savings of about 5000 GWh even after regular growth in consumption of residential sector due to demand drivers.

The article presents an approach to substantiation of strategic decisions in the field of power sector technological transformation. The approach discussed is based on multi-criterial evaluation of the effects of such transformation obtained with the help of optimization models used for the least-cost choice of the electricity generation mix and financial models used for assessment of financial stability of different technological segments of the power sector.

In day to day life, with an ever-growing demand in power sector, planning and operation plays a vital role in providing an economical, reliable and efficient electricity to the consumers. In this regard, unit commitment (UC) plays a significant part in daily planning and optimal scheduling of generating units so as to meet the hourly load demand in an efficient manner. This paper focusses on presenting a robust and effective methodology for solving the UC problem using GAMS simulation environment. In this work, to assess the effectiveness of GAMS over MATLAB environment, 3 and 4 thermal generating units with and without spinning reserves and ramp rate constraints have been considered over 24-hour time horizon.

The distributed generation resources are expected to largely transform the future operation of distribution systems. However, there is high perception for wider integration considering how evenly the distributed generation resources benefit are distributed among various agents in the power sector. This study presents a multi-objective planning of Distributed Generation to determine the best options for siting and sizing and different types of Distributed Energy Resources (DER) considering multi-agent participation. The developed multi-objective optimization method adopts the Strength Pareto Evolutionary Algorithm 2 (SPEA 2) technique, with the objective to promote and distribute benefits of Distributed Energy Resources among participating agents such as Distribution Network Operators and Distributed Generation Developer, and with the expectation that the prospective benefits from the distributed resources will speed up the current regulatory proposal updating in the electric sector.

The Nigerian power system is characterized by huge gap between supply and demand. With electricity demand projected to increase with the population, growing at an annual average of 2.5%, the imbalance between generation and demand is bound to persist unless urgent strategy planning of the generation and transmission infrastructures is pursued. The REPLAN project proposes multi-region power system planning approach to help deliver insight into the long-term development of Nigerian power sector. REPLAN utilizes the regional energy resources and load demand to optimally fashion out generation capacity mix for inter-connected regional grids, capable of operating independently for Nigeria. A multi-region optimization model is developed to investigate the long-term development of the regional grids over a timeframe from 2015 to 2050. The results of the simulation experiments conducted on different scenarios show the suitability of the developed model for predicting the optimal pathways for inter-regional grids for Nigeria.

In this work a drone has been used as a surveillance unit. It is preprogrammed to follow the electrical route using GPS module and monitor any illegal connections. Once it detects any illegal connection it operates an inbuilt telescopic extension mounted cutter and terminates the illegal connections. It also monitors the temperature of distribution transformers along with the current drawn from it using thermographic camera and current measuring device. In case of any abnormalities in temperature or current drawn of the transformer it generates an alarm and conveys it to the local operating station. By the use of such a surveillance system the losses incurred by the power sector can be reduced drastically and also the system prevents detrimental effects arising from transformers.

Cloud-to-Ground (CG) lightning in Guangdong Province, South China has been observed over decades by the Lightning Location System (LLS) operated by power sector in China. In this paper, we present the characteristics of CG lightning based on the data collected during 2004–2017 when the LLS performance was relatively steady from year to year. To the best of our knowledge, it is the first time to investigate CG lightning from such a long period in this area. Over 30 (67) million CG lightning flashes (strokes) were recorded during this 14-year period. Various characteristics, including flash density, peak current, multiplicity, ratio of positive CG lightning, lightning day, etc, are investigated. Interesting spatiotemporal patterns of the CG lightning parameters are obtained and the potential causes are discussed.

At present, as per January 2019 scenario, Indian power sector has about 76 GW of Renewable Energy Sources (RES) out of total installed generation capacity of about 350 GW. Based on confidence of handling such large and complex integrated power system, in this context for the road ahead, multifarious studies have been carried out further with demand as projected upto 2022 and 2027. These studies consider more and more renewables with gradual phasing out of conventional fossil-fuels based power stations. The capability of the system to operate in a reliable and secure manner with non-fossil-fuels based capacity with penetration of 49.3% and 57.4% in 2022 and 2027 respectively has been established to serve the requirement of power and energy. Accordingly considering intermittency and energy content it is estimated that India’s Intended Naturally Determined Contribution from sources other than fossil-fuels would be to the tune of 40% by 2030.

Machine learning is applied in almost every field of knowledge in recent years. Renewable energy domain now extensively uses machine learning to provide farmers and grid operators with proper and timely information about solar irradiance prediction for future planning. Connecting grids with solar energy systems has brought unprecedented shift in the power sector. Nevertheless, the intervention poses challenges including intermittency that affects the overall energy supply and demand management. Our proposed solution intends to make prediction models using Machine Learning techniques (Linear Regression, Regression Trees and Support Vector Machine) which uses the past weather data including the parameters such as temperature, wind speed, atmospheric pressure, and humidity and predicts solar irradiance for the future. The model can help the grid operators for improved supply and demand management.

Electric Vehicles are opening a promising field of engineering research which is very innovative and promising due to increasing consumer swiftly. As like other developed countries, Bangladesh is also experiencing with the use of battery electric vehicles similar to easy bike, auto rickshaw and electric bike. However, the charging stations are not sufficient and hence the electric vehicle batteries are frequently recharged from the residential connection. Due to the huge electricity consumption throughout the country, the power sector has been dropped into higher system loss and failed to earn profit from this sector. In this paper, fuzzy logic based energy management algorithm is developed for electric vehicle charging station in Bangladesh. The fuzzy optimization techniques provide different charging rate for different conditions. It will save energy and makes electric vehicle business profitable to the owner.

Trabajo presentado en el 6th International Conference on Control, Decision and Information Technologies (CoDIT), celebrado en París (Francia), del 23 al 26 de abril de 2019, The solar PV power sector in Spain has been developing at a spectacular rate in recent years. The energy cost and the dependence on fossil fuels can be reduced by improving the efficiency of photovoltaic energy production. The performance of a solar radiation conversion system is affected by a tilt angle with the horizontal plane. Thus, the photovoltaic array needs to be tilted at the correct angle to maximize the performance of the system. In this paper, we found the optimum tilt angle and applied for Barcelona, Spain, located at latitude 41o 22' 56'' North and longitude 2o 6'56'' East. The optimal tilt angle for Winter (December, January, February) is 56.46 and the optimum tilt angle for Spring (March, April, May Ls 2 .11¿and the optimum tilt angle for Summer(Jun, July, August Ls 13.76¿ and the optimum tilt angle for Autumn (September, 2ctober, November Ls 8.1 ¿. finally, the annual optimum tilt angle for our latitude Ls 36.87¿, ZLth thLs optimal slope angle, maximum monthly and annual solar radiation is calculated. In this way, we can increase the energy generation when achieved to maximum solar radiation. With this process, we were able to increase 10.54% of energy., This work has been partially funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the projects DEOCS (ref. MINECO DPI2016-76493) and SCAV (ref. MINECO DPI2017-88403-R).This work has also been partially funded by AGAUR of Generalitat de Catalunya through the Advanced Control Systems (SAC) group grant (2017 SGR 482).

Today, in the era of Industry 4.0 with total automation of the cloud data bus and domestic energy production the concept of the Virtual Power Plant (VPP) is entering global power sector to facilitate the integration and management of distributed power units relying on real-time communication and uniform control. The motivation behind VPP is to solve a problem of variable profile and uncertainty of power generated by DG units that is found to be challenging when building reliable DG-aided power plant. This paper aims to propose the potential location for the VPP in Kazakhstan and to recommend roadmap planning for its realization based on the results and estimates conducted in the scope of simulations. It was revealed that there is promising possibility to locate VPP on the territory of South Kazakhstan, Jambyl and Almaty regions due to concentration of high capacity renewable energy plants and efficient operation of Energy Management System (EMS) revealed from the simulation results. Emergence of the VPP may contribute to further development of the renewable power grid provided financial aid to facilitate technologies and to promote the prosumer status of households is attracted.

Energy or Power is one of the most valuable assets of any country today. The economy of a country largely depends on power as industries cannot function without it. This paper briefly talks about how power is generated from different sources in Pakistan and the challenges faced by the power sector today. The data presented are from the four major power producers KESC, WAPDA, AEC and IPP's. In addition, it also discusses the current production of the installed systems, their total production capacity and presents a feasibility study of different sources from economic, environmental and political standpoints.

Public Private Partnership (P3) is used globally in the power sector. It is usually called Power Purchase Agreements (PPA) in the Power sector. It is a relatively new delivery method in infrastructure project. It is an updated version of the Build Operate Transfer (BOT) delivery method. Renewable energy PPA are very common because of the high construction cost. They have low operation and maintenance cost which make the overall life cycle cost is low. It gives a way for the developer to get their investment back with a reasonable profit. It helps the owner get the power with low or no initial cost. The risks associated with the PPA method are different from traditional delivery methods. Identifying and understand such risks is a key in the success of PPA projects. It can make such method a viable option to many countries. This paper presents and analyzes different risks in P3 projects in addition to solutions to mitigate such risks.

The increasing power demand in the modern power sector makes inversion of two or more HVDC links in to the same AC system inevitable leading to a multi-infeed HVDC (MI-HVDC) system. With LCC-HVDC, the problems of inversion into weak systems are more pronounced in MI-HVDC systems. These difficulties can be overcome by forming a hybrid MI-HVDC system with one link LCC-HVDC and the other as a hybrid link with a thyristor based rectifier and voltage sourced converter based inverter. The hybrid LCC-VSC link needs a thorough study for its application in multi-infeed systems. This paper emphasizes on a comparative study of different controllers of VSC inverter of the hybrid HVDC link in a multi-infeed application. The simulation study is carried out in the PSCAD/EMTDC environment.

This paper aims to study the momentum strategy in Telecom and Power sector in two time windows (1) 5–5 momentum strategy and (2) 8–8 momentum strategy. Thirteen companies in Telecom sector and Fourteen from Power sector that are listed in Bombay Stock Exchange were studied. The adjusted closing price data of these companies was collected for the period of 2009–2017. This study adopted the Jegadeesh and Titman methodology and the empirical result shows that momentum strategies have Positive returns in Telecom sector but, in Power sector momentum strategies have Negative returns.

This is a set of work-in-progress exploratory studies dealing with the log analysis and correlation of very specialized setups in industrial control systems implemented in the context of power systems. These cases consider the behavior of logs and their ability or inability to shed light on the incriminating nature of a criminal investigation. Our research is novel and unique in the sense that no such previous study exists detailing the forensic investigation on ICS within power sector.

At present, power theft ways become increasingly subtle and intelligent. Power theft not only has caused a great loss to the nation and the power sector, but also has brought serious security risks to the equipment and personal health. Although the power theft behavior of the energy meter voltage transformer secondary circuit has been well recognized and effectively suppressed, the anti power theft method for the secondary circuit of the energy meter current transformer is still a weak link. Therefore, this paper proposes a transient method based anti power theft method for the secondary circuit of the energy meter current transformer. This method applied the pulse signal to the secondary circuit of the energy meter current transformer first, then obtained the equivalent resistance and inductance parameter of the circuit by measuring the transient value of the circuit response current. Comparing these parameters with the original parameters of the circuit, we can judge the circuit state and power theft way. The simulation results verify the accuracy and reliability of the proposed method, which is a new anti power theft method of the energy meter.

A major challenge in the power sector is about to take place since the main Japanese and Asian car manufacturers have announced that all manufactured cars from 2017 will be battery powered. Main effect of increasing the number of Electric Vehicles on power systems is the creation of a significant domestic demand for electricity. Electric vehicles are in the forefront of emerging zero emission technologies that are essential for a sustainable future. Due to the fast growing demand for electric vehicles, it will be a key point to consider when managing the power utilization in Sri Lanka. As peak demand is heavily catered using diesel power, commercial and environmental success relies on concentrating vehicle-charging activities to non-peak hours. An intelligent interface between electricity supply and electric vehicle will help to optimize the electricity demand and reduce the weight at peak demand time. This research worked towards the design and development of a cost effective, high accuracy intelligent socket outlet for charging of electric vehicles to minimize the effect of electric vehicle charging on national grid, hence reduce the environmental and economic impact. For the intelligent determination of charging time, an algorithm has been developed based on historical demand data, existing charge of the battery and the user requirements.

This paper presents a study aimed at evaluating and comparing the performance of five selected solar resource monitoring stations in the Kingdom of Saudi Arabia (KSA). Also, present an overview of the current electricity demand since KSA's power sector relies heavily on liquid fuels. The data used in this study have been collected from the new solar atlas which was launched by KACARE for collecting the solar data along with other parameters through the installed stations across the country. The results showed the potential of solar irradiance during the year for different places which would contribute to the implementation of plans for renewable energy (RE) projects. The Selected City in the Northern region of KSA has the highest amount of solar irradiation with an approximate annual of 82450.5 Wh/m2/year, followed by the southern city with 73199.1 Wh/m2/year. Also, GHI and DNI data were compared to the earlier solar atlas data which was published by NREL in 2002 and they were in close agreement with less than 10% difference.

Plenty of literature exists about how to model liberalized electricity generation markets for the medium and long terms, contributing to the analyze and understanding of those markets, helping companies to plan cost-efficient shortterm market strategies and/or long-term generation capacity investments, and supporting regulators and policymakers in policy decisions and market designs. However, those models do not explicitly consider the impact on investment decisions, mix of technologies and wholesale market prices; of policy decisions but as an external passive input to the model. This paper reviews existing approaches to model policy decisions in such a context, and provides a theoretical modeling framework that explicitly considers the interaction of policymakers' decisions with the generation investment and operation, and customers' response in a liberalized power system. Such kind of model, based on bi-level optimization, contributes to the longterm assessment of some policy decisions in the electricity sector.

The power sector is in its fast growing phase to meet the growing demand for electricity. With the integration of Distributed Energy Resources (DER) in the Distribution Network (DN), the conventional network has been upgraded from a passive network to an active network. With high penetration of DER the network experiences high R/X ratios, unpredicted variation of source with continuously variation of loads. With all these challenges power grid is committed to provide good quality power to the consumers and maintain the stability of the network. Hence, to analyse the performance of the network, load flow studies are very important. This paper compares the performance characteristics of Newton-Raphson (NR) method and Forward / Backwards Sweep (FBS) method with a variable load pattern. The performance of the methods are evaluated in an IEEE 13 node test feeder. The performance characteristics are evaluated for their different convergence criteria by increasing the R/X ratio, by varying the tolerance values and analysing the voltages at break points. Based on the case studies the results show that FBS method is more preferable for Distribution System.

This paper attempts to emulate Phasor Measurement Unit (PMU) for Static Security Analysis of power systems, PMU's are enablers for real time and near real-time analysis of the power system. They are being integrated into the power system for enabling enhanced monitoring and control of the network. A methodology is presented for emulation of PMU and storage layout of data obtained from the emulation. A technique enabling the emulation of the PMU's specifically for Static Security Analysis will be of great use for analysis of the system by the researchers and scientists working in the power sector. Newton-Raphson will be used for solving the non-linear power flow equations while emulating the PMU in this paper. Emulation of IEEE 14 bus test systems has been demonstrated using the proposed method in MATLAB and the results obtained are presented in the paper.

This paper presents, the importance of pump storage system for continuous and reliable supply without any loss of load has been determined. Two different case studies have been analyzed using present approach. The first case includes without pump storage and second case is with storage green energy microgrid. The optimal capacity of the pump storage has also been determined. The present approach has been validate and tested on interconnected 3-microgrid system with green energy generation.

This work has been conducted in order to develop a Generation Expansion Planning model based on Dynamic Systems to come up with a new approach to be applied to the Brazilian generation system regarding the one currently used. Moreover the new model intends to become a flexible tool to evaluate scenarios regarding the power sector evolution. Dynamic Systems have a wide range of applications. The use of these tools has been gaining success in the power sector by their ability to observe and model interdependences and feedbacks between the different system variables. This kind of approach was then implemented in many power systems. The work is introducing new features to this approach based on specific characteristics of the Brazilian Power System, namely: the large penetration of hydropower and the possibility of energy storage; seasonality of power generation; existence of electricity submarkets with transmissions constraints between them. The results obtained so far show that the Dynamic System developed can represent in good conditions the main features of the Brazilian system, whereas it identifies and correctly shows patterns of water management and energy prices that comply with the reality. These results show that the approach under development can become a valuable asset for both public entities that perform long-term plans and for power system agents.

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a longterm national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions-native resolution (134 BAs), state-level, and NERC region level-and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.

With increasing stress over transmission lines and non-availability of electricity at remote locations; Distributed Generation (DG) has emerged as the best option for utilities. DG includes conventional and non-conventional energy resources. This paper presents the various factors concerning the integration of DG in electrical power systems. These include environmental; commercial and technical issues. In this paper; the main focus has been given to the Indian power sector and the initiatives taken by the government to increase the penetration of DG based on renewable energy. The role of various technical institutes/centres; which work under the Ministry of Renewable Energy (MNRE) for resource assessment and different financial institutions which provide monetary assistance to set up non-conventional based DGs; are discussed in this paper. This paper also highlights the various schemes launched by the government to promote DG. It will benefit the academia and the industry to systematically understand the scope; potential and the government commitment to promote various available non-conventional energy resources in India.

Energy storage seems set to play a key role in the transition to a low-carbon economy. The achievement of 2050 carbon emission targets set by the EU (emissions should be cut to 80% below the 1990 levels) will require an important electrification of the transport and heat sectors and also the decarbonisation of the power sector. Thus, the aim of this paper is to evaluate the different emerging business models regarding energy storage systems applicable in three case studies: power (distribution utilities); transport (electric vehicles for domestic use); and heat (heat pumps in residential buildings) sectors. A review and discussion of potentially relevant business models is undertaken in order to analyse the diverse frameworks (including innovation) and their suitability to the case studies. This will highlight the kind of services to be offered, how these services create value and how this value can be monetised. The main challenges in the implementation of energy storage (with a focus on market and regulatory issues) are also evaluated. This study will identify the emerging business models with the highest value and the related challenges within each of the three case studies.