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Several countries have a critical need to enhance their electricity production to satisfy the tremendously increasing energy demand and to minimize the black outs. Due to scarcity of fossil fuels and degrading environment, rooftop Solar Photovoltaic (SPV) can be a suitable renewable alternative of green and clean energy. In this paper, due to the techno-economic, environmental and social benefits of Solar PV, the modelling and planning of a solar PV plant to fulfil the energy demand of an academic building is carried out. The analysis is done including all the financial and environmental aspects considering recent market prices and future price escalation. A Modified Greedy Search based optimal planning of the SPV to minimize grid dependence considering load variation pattern with its assessment analysis for an academic building is proposed in this research work. The various financial parameters that affect the feasibility of Solar PV plant i.e., energy payback period, grid dependency, rate of investment return, economic payback period, rate of escalation with actual cost of electricity, annual maintenance cost, depreciation and taxation are considered and evaluated. The environmental factors related to the generation from Solar PV i.e., CO2emission reduction and carbon credit are also included in analysis. The results obtained for the proposed Solar PV plant shows that the energy payback period is 8 years and IRR with depreciation and taxation is 21% (approx.) with net CO2mitigation of 1199 tCO2during the useful life span (25 years) of the plant.

ABSTRACTMobility has modernized urban areas using an efficient transportation system. However, mobility demand growth has accelerated the expansion of conventional transportation, which significantly contributes to pollution. The need of Green transportation results in the eminence of electric vehicles (EVs). Besides, green mobility minimizes pollution from transportation systems and conventional power sources when EVs are optimally integrated into the utility grid. Thus, this study assesses different significant optimum possibilities of grid-connected EVs. A review of the critical impacts of grid-tied EVs is presented. Vehicle to the grid (V2G) is the future of electric cars. This uses a bidirectional power flow of the EV’s battery charging to either charge the car or sustain the utility grid. The V2G is highly affected by diverse loading conditions that challenge the network’s acceptable voltage and optimal power-sharing within the electrical network. It is observed that the V2G perspective is based on the 5Ds (decentralisation, de-carbonization, digitalization, deregulation, and democratization) vision to overcome the overall shortcomings in the modern power grid. The 5Ds vision of V2G implementation sustains different stakeholders working on the future of electric cars. Thus, this research is a stronger foundation for the new perspective and vision of V2G development and applications.

This paper presents a day-ahead forecasting method for photovoltaic (PV) power plants in commercial sectors. The method is based on numerical weather prediction (NWP) models from open weather maps and power plant specifications. The output of the model is the predicted power output from the PV power plant, which is incorporated into an optimal control strategy of the PV plant using battery storage. The use of optimal algorithms assists in the PV power plant curtailment in cases of over-generation and reduces the dependence on conventional power sources such as generators in cases of under-generation by the PV plant. It was found that most forecasting methods do not incorporate PV power and storage systems for proper optimization and demand management. This can be seen as a gap for further research of forecasting models integrated with battery storage systems to improve PV power system performance. Results obtained show a good performance of the developed model. A root means square error (RMSE) of 425.79 W and 595.10 W and a mean absolute error (MAE) of 246.26 W and 238 W were achieved for a summer and winter day, respectively. Furthermore, an excellent positive correlation exists between the predicted output power and the observed results, with R2values over 90%.

ABSTRACTExponential increase in global energy demand has led to the extensive integration of renewable energy resources. Solar energy has particularly attracted major interest, due to its scalability and ease of installation. A rise in solar insolation levels in the gulf-region has led to the rise of solar integration within the energy mix to provide strategies for clean energy production. Furthermore, GCC countries implemented various strategies to increase the installed capacity of photovoltaic system installations to cope with the rapid consumption of energy by consumers. In this review, the highlighted progress in solar energy development is discussed with respect to the gulf-situated countries. Present diversification of implemented and future projects paves the way to successful green energy integration. Furthermore, present challenges with photovoltaic (PV) implementation within the region such as oil dependence and arid climatic conditions affect its performance dramatically. However, the potential impact and benefits are numerous, which in hand encourage photovoltaic implementation within the region. In addition, measures are discussed for the steady improvement of solar energy integration within the electrical network, to be considered by the countries situated within the region.

This paper develops a new multimode control strategy for power quality (PQ) improvement in distributed generation (DG) units that employs a voltage source converter (VSC) as the electronic interface medium. The devised control strategy seamlessly operates for both the grid connected (GC) and autonomous/stand-alone (SA) modes of microgrid (MG). A novel computationally efficient comb-filter driven discrete time oscillator is developed for current reference generation (CRG) under GC operation. It constitutes a cluster of zeros to introduce notch peaks at integer multiples of the fundamental frequency thereby ensuring improved harmonic rejection capability. Consequently, it ensures unconditionally balanced and sinusoidal grid currents with improved PQ to comply with grid interconnection codes prescribed in the IEEE std-519 and std-1547 even under electrical anomalies. In the SA mode, the CRG scheme is developed in a stationary reference frame with an improved vector proportional integral (VPI) compensator. Despite the uncertainty of load parameters, the proposed VPI guarantees zero steady-state error and superior transient response. A finite state machine-based synchronization framework is proposed to ensure secure and seamless transfer of MG between GC and SA even under disturbances. The practical viability of the proposed multimode control has been demonstrated by applying various switching rules in both GC and SA modes of MG operation.

ABSTRACTA design process for determining the impact of the simple wake model, park (WAsP) model, and the eddy-viscosity model on the energy production of large offshore wind farms is presented in this study. This process is implemented in the system advisor model simulator. Even though wind turbine components’ electrical transients and physical stress are not covered in this simulator, four large offshore wind farms are successfully simulated. It is found that the simple wake model is more suitable for controlling wake effects on large offshore wind farms than park (WAsP) and eddy-viscosity models. This model produces higher annual energy with a better capacity factor than the other two models. Furthermore, although any generator system could test these wake models’ performance, this study uses single stage low-speed and direct-drive generators. The direct-drive generator produces higher annual energy and better capacity factor on all four offshore wind farms for all three wake models. However, this performance is for a rectangular or square layout of wind turbines on the wind farms, with row orientation 0° and every other row as offset type. This study’s findings significantly optimize wake effect control and wind turbine layout design on large offshore wind farms.

ABSTRACTOwing to the rapid incorporation of doubly fed induction generator (DFIG)-based wind farms into the power system, the sustainability of the power system has been a major concern of system planners, operators, engineers, etc. This has necessitated a proper investigation to be implemented in the stability of the power system. The small-signal stability analysis can be used to predict the dynamic behaviour of the power system and the sustainability of energy with the application of DFIGs. The state-of-the-art of DFIG, its impacts on small signal stability and the potential effects are proposed in this paper. The control techniques on DFIG to enhance damping qualities of the power system are also presented. This paper reviews the small-signal stability analysis of wind power system integrated with DFIG-based wind farms. The developments that have been made till-date towards attaining models of DFIG-based wind farms will give a definitive conclusion about small-signal stability. The prediction methods and impacts of integrating DFIG-based wind power into the power system are reported together with their limiting factors. Lastly, the techniques that have been presented in the paper will improve the small-signal stability and guarantee the future sustainability of power supply.

In practice, nonlinear electrical loads pose various power quality (PQ) challenges. Driven by these challenges, a parallel combination of a nonlinear load and a photovoltaic (PV) inverter with adaptive quantum normalized-least mean fourth (qXE-LMF) filter is proposed and experimentally validated to detect and compensate for the harmonics in harmonically contaminated currents. A scheme with an adaptive qXE-LMF using fundamental weight components is used to generate the harmonics in the inverter output current thereby improving the PQ of the grid supply. The resulting grid current is pure and balanced; the PV inverter connected in parallel with the nonlinear load provides reactive and harmonic current support. Practically, the adaptive feature enables the online learning of filter weights of the load current harmonics to guarantee unconditionally balanced sinusoidal grid current. The proposed qXE-LMF filter ensures fast convergence and minimum steady-state oscillations in the grid reference currents. An improved anti-windup PI compensator is used to ensure dc-link voltage stabilization. The practicality of the proposed adaptive qXE-LMF filter is experimentally demonstrated using a three-phase four-wire uncontrolled rectifier-based nonlinear load. The experimental results also demonstrate the robustness of the qXE-LMF filter against changes in solar insolation level and nonlinear loads.

Maximum power point (MPP) tracking algorithms have always been at the forefront in photovoltaic (PV) systems to counter the nonlinearity caused by PV arrays and, thereby, harvest maximum power. There are several MPP trackers, including fixed and variable step size. The application of a fixed step-size MPP tracker leads to steady-state power oscillations around MPP. On the other hand, a conventional variable step-size MPP tracker employs a constant multiplying factor to increase the convergence rate; however, its response is found to be sluggish under PV parameters’ uncertainties. Therefore, in this article, an optimized fractional nonlinear synergetic controller (FNSC) driven MPP tracker is proposed to meticulously detect the true MPP. The proposed optimized FNSC provides a large dynamic range and ensures minimal sustained power oscillations around MPP even under unequal irradiances. The algorithm based on fractional calculus utilizes macrovariables for improving the performance of the proposed FNSC under steady-state and dynamic operating conditions. The effectiveness of the proposed optimized FNSC is verified using OPAL-RT (OP5700). The outcomes of this study validate the practicability of an FNSC-driven MPP tracker to guarantee less MPP tracking time. The MPP tracking time recorded with the proposed FNSC during steady-state and dynamic conditions is less than 21.80 and 20.80 ms, respectively. Besides, it guarantees 99.7% tracking efficiency and, thereby, outperforms the existing MPP trackers.

Fossil fuels are rapidly running out, and with the demand for environmentally friendly energy sources increasing, power grids are looking for distributed power generation-based renewable resources. The distribution of these energy sources is significantly linked to the development of smart microgrids, which are also extensively connected with the energy internet. This paper explores the energy internet operation, focusing on developing a routing algorithm for an energy router. The energy routing algorithm is further substantiated with the aid of simulations. This algorithm can find all the paths available for energy transmission between two nodes and selects the track with the most negligible losses as the path for transmission. All the possible routes are displayed along with the losses associated with each direction to ensure that the approach with the lowest losses is taken. The algorithm is also tested for 24 h at an hourly interval to observe the change in power transmitted on the system.

Developing countries are experiencing significant urban and population growth. This amplifies the crisis of governance of essential public services. This study analyses the electricity market in Lubumbashi, one of the Democratic Republic of Congo (DRC) municipalities. Surveys at different scales are conducted, assessing both access to electricity and the role of actors. 5270 households, 41 policymakers and 100 employees at different scales are interviewed. It has been found that the electricity market is deteriorated by illegal connections to the electricity grid, uncontrolled urban growth, corruption, and poverty. Besides, the quality and cost of electricity decrease with distance from the city centre. Therefore, privatization of the electricity sector would lead to low-cost electricity and high-quality service.

Integrating energy systems with information systems in smart grids offers a promising avenue for combating electricity theft by leveraging real-time data insights. Suspicious activity indicative of theft can be identified through anomalous consumption patterns observed in smart networks. However, a smart model is required for capturing and analysing the data intelligently to accurately detect electricity theft. In the paper, electricity theft has been detected using an encoder-decoder-based classifier that integrates two models of convolutional neural networks (CNN). The aim is to scan the strength of the data and built a smart model that analysed the connections in complex data and determine the pattern of theft. The model comprises three compartments: the auto-encoder, the wide convolutional neural network (1-D CNN model), and the deep convolutional neural network (2-D CNN model). The auto-encoder has been trained on the complex and in-depth linkage between the theft data and the normal data as it removes noise and unnecessary information. The 1-D CNN model gathers relevant connections and general features, while the 2-D CNN model determines the rate at which energy theft occurs and differentiates between the energy-stealing consumers and normal consumers. The efficacy of the approach is underscored by its superiority over traditional deep learning and machine learning techniques. This paper elucidates the distinct advantages and applications of the proposed model in combating electricity theft within smart grid environments.

This study presents a strategy to optimize hybrid power system dispatch for commercial sectors in South Africa while utilizing the day-ahead method to forecast solar photovoltaic (PV) power. The approach utilizes numerical weather prediction (NWP) models obtained from open weather maps and incorporates power plant specifications to generate predictions of the PV power plant’s output. These predictions are then integrated into an optimal control strategy incorporating battery storage. The use of optimal algorithms helps manage PV power plant curtailment during periods of over-generation. It is crucial to optimize PV power systems and ensure a continuous power supply for solar power plants, even during unfavorable weather conditions. Besides, the study develops a model that solves the challenging questions of combining solar power forecasting with an optimal dispatch and demand management scheme. Therefore, there is a need to incorporate battery storage systems through the developed optimal control method to maximize the energy from the PV system and minimize the power from the utility grid. The obtained results demonstrate the effectiveness of the developed model. The winter season presented a lower MAE of 21 kW, an RMSE of 35.4 kW, and a MAPE of 3,1% for PV power output forecasting, showing that the errors during prediction are lower compared to other seasons. It has been observed that 60% of the load is supplied through a combination of PV power and battery storage. Therefore, evidence of the developed optimal hybrid power dispatch with an innovative solar power forecasting model suggests that accurate forecasting can improve system planning and mitigate the necessity of procuring grid power at high electricity prices.

A typical 2 × 25 kV traction power supply system consists of both primary and secondary equipment housed in control rooms, and the traction overhead wiring (OHW) that runs between the substations. The substation secondary equipment consists of the protection and control intelligent electronic devices (IEDs) known as relays. Each section of the OHW between the substations is protected by a set of two relays at both ends of a line for impedance protection and their backup relays. At substations facing the sections at the end of the line, where there is no other substation on the other end, usually the overcurrent and earth fault protection is used. At the substations, there are disturbance fault recorders installed or relays equipped with a capability to record and store disturbance fault records. An analysis of these fault records makes a significant contribution to the efficient running of a traction system such as the Gautrain rapid rail system. A combination of the analysis of the faults that occur in the OHW as recorded and stored in the relays as well as the performance of the IEDs and the protection settings using the on-site tests are a subject of this article.

ABSTRACTRenewable sources such as solar PV and wind are stochastic in nature, hence their integration with emerging isolated microgrid (MG) is challenging especially with regards to stability issues. An accurate prediction model of wind and solar sources is necessary to analyze the uncertainty in MG system and to encourage the reliable participation of wind and solar power in the energy market. The advancement in deep learning methods has made it possible to develop a multi-step forecasting model unlike shallow neural networks (SNNs). The time series forecasting using SNN and Recurrent Neural Network (RNN) suffers from the problem of vanishing/exploding gradient while training. To eliminate this problem the long short-term memory (LSTM) RNN has been used in this study for wind speed and solar irradiance prediction. The forecasted solar and wind power is applied to analyze the load frequency behavior and the response of nonrenewable sources for sudden rise and fall in load power demand and PI controller is used to mitigate frequency deviation to ensure the stability of the MG power system.

This article presents an optimal control scheme based on model predictive control (MPC) strategy for a photovoltaic (PV)/battery hybrid system. By considering various trading scenarios of electricity markets in order to maximize profits, an objective function is formulated using variable electricity tariff (VET), battery state of charge (SoC), and availability of solar insolation. The proposed optimal scheme is designed with a two-stage control algorithm based on VET, forecasted solar insolation, and SoC to easily cope with the load demand variation between low and high prices. In this case, the MPC is implemented to predict the SoC in the PV–battery hybrid system by directly calculating it in the first stage while predicting the values of solar irradiance, load consumption, and electricity price. Furthermore, the proposed MPC is used to account for forecasting errors and acts under the given limits to minimize errors and compensate reactive power during the scheduling process. To validate the performance of the proposed control scheme, the PV/battery system is modeled and implemented in MATLAB/Simulink package. Simulation results demonstrate that the proposed optimal control scheme has better performances under various scenarios such as parameter uncertainties and sudden changes.

Several features of innovative grid technologies can be deployed for the overall performance of the power system environment. This can be seen from the generation to the consumption of energy. The two-way communication of smart metering introduces the novel functionalities of the energy management system. This paper presents a practical implementation of using the intelligent metering system. It consists of implementing a nanogrid that optimally coordinates the energy from the solar panel, battery storage and utility grid to supply the end user. The developed model is validated with an optimal value of the state of charge of the distributed energy storage to maximise energy from the solar panel and battery storage while minimising the power received from the utility grid. A demand response scheme is employed to formulate the performance index of the energy management system using three optimal control models: adaptive open-loop control, adaptive closed-loop Control and model predictive control schemes. The formulation of the performance index of each approach is a function of the energy flow from different resources depending on the power consumption. The three models have given different insights into the performance of the smart nanogrid, which may be used to the Advantage of the grid owner or end user. Through the performance of the optimal strategies, it can be observed that energy management is ensured, and real-time monitoring of the entire system is guaranteed. The performance models facilitate the minimisation of the power from the utility, resulting in savings between 23.7 % and 39.240% of the total energy demand from the end user. Besides, the system design is validated by an electrical system to form a real-world innovative nanogrid application in residential environments.

This paper presents the optimal energy management approach with optimum sizing of the battery storage system (BSS) for the minimal possible total operating cost of the considered nanogrid. The five various operating modes are tested to achieve the optimal operating mode on an hourly basis. Linear programming (LP) is used to get optimal solutions for objective functions having non-integer variables whereas mixed-integer linear programming (MILP) is used to optimize the objective function having an integer variable. The proposed hourly-based optimal operating mode produces 17.8–94.5 % savings in the day operating cost compared to the best individual operating mode. The optimal capacity of the battery storage system is also derived by using the proposed operating modes. The achieved optimal capacity of BSS based on the day operating cost is further modified with the help of investment cost and its interest paid during the life span which suggests that the optimal capacity range will be 4–19 kWh for this nanogrid.

With affordable and clean energy being one of the Sustainable Development Goals (SDG7), most developing economies are still caught up with the dilemma of inadequate power supply and heavy dependence on fossil fuel. This social menace is premised on rapid population growth, industrialization, modernization, etc. Even though these sources of power appear to be far-fetched from being sufficient, they are noted for creating a significant level of environmental pollution, global warming, and health-related risks. The Conference of Parties 26 (COP26) assembly held in Glasgow, United Kingdom, stressed the need to bring down the rising annual global temperatures to 1.5°, with developing economies having a significant role in achieving this target. This article has presented a review with insight into certain power generation metrics within the context of (SDG7). This span across the investigation of different energy modelling tools, their depth of effectiveness, the general pros and cons of energy policies premised on these tools, and progress made so far towards the development of an affordable and clean power sources mix in developing economies. A deduction was reached that there is an immense potential for power generation from affordable and clean energy sources as this bridges the enormous gap between power demand and supply as well as mitigates greenhouse gases (GHGs) effects.

Low-carbon economy, environmental concerns and fuel efficiency demands have placed strong emphasis on the fossil fuel based power plants, requiring them to operate at high efficiency. A number of methods have been applied in the power generation industry to improve boiler efficiency and reduce the emission by optimising the combustion process in many power plants. At the same time, computational fluid dynamics-based numerical simulation methods are applied to evaluate the performance of the combustion. However, the frequent variety of fuel quality and changing conditions inside boiler make the efficiency and emission-related combustion problems still occur and plague the electricity generation industry by impairing the boiler efficiency and increase more concerns caused by deteriorated boiler combustion process. This research proposes new methods based on integrating real-time simulation with online learning technology to improve the power plant boiler combustion process.

Controversy exists regarding aortic root reconstruction in the management of acute type A aortic dissection (AAD). One hundred fifty-four patients (mean age 56.9 ± 11.3 years) with AAD had surgical repair between 1996 and 2007. Group 1 (n = 110) required no aortic root surgery. Seventy-one patients had ascending aortic replacement. The aortic valve was repaired in 37 patients (34%) and replaced in one. Group 2 (n = 44) had aortic root surgery. Thirty-four patients had composite root replacement, and seven had a valve-sparing root replacement. Root reconstruction and separate valve replacement was accomplished in three. Hemiarch replacement was included in 39 (35.4%) Group 1 patients and in 12 (27.9%) Group 2 patients. Forty-nine of the 154 patients presented in cardiogenic shock. Multiple risk factors for operative mortality were analyzed. The overall operative mortality was 9.7 per cent: 11 per cent for Group 1 and 6.8 per cent for Group 2 (P= NS). By multivariate analysis, preoperative shock (P= 0.03, odds ratio [OR] = 5.48), postoperative ventricular arrhythmias (P= 0.002, OR = 4.62), and packed red blood cell transfusion (P= 0.002, OR = 1.15) were independent predictors of hospital death. Prompt surgical treatment of AAD before cardiogenic shock ensues can improve the outcome of patients. When indicated, aortic root surgery can be performed without increased mortality and morbidity.

Background and Purpose Evaluation of subclinical atherosclerosis by B-mode carotid ultrasound intima–media thickness (IMT) is an endorsed technique whose ease and precision is improved by use of automated IMT measurement algorithms. We report results of a validation study of SonoCalc, an automated IMT software program.Methods Three vascular sonographers measured the mean common carotid artery IMT twice of 120 near and far wall CCA segments from 30 subjects by manual electronic instrument calipers and with SonoCalc.Results Accuracy analysis indicated the equivalence of SonoCalc IMT measurements to those with manual electronic instrument calipers (p< 0.0001). The coefficient of variation (CV) was calculated for each set of duplicate SonoCalc and manual electronic instrument calipers measurements. The average SonoCalc-manual electronic instrument calipers CV differences significantly favored SonoCalc (p< 0.0001).Conclusion This study demonstrated that the use of the SonoCalc and the manual electronic instrument calipers produced measurements whose differences were statistically insignificant. Furthermore, the analysis to assess reproducibility of the two methods showed that the SonoCalc method was significantly more reproducible than the manual electronic instrument calipers methods.

Transesophageal echocardiography with use of a uniplane phased-array transducer with a transverse or horizontal scanning plane has become a well-established tool for evaluating cardiovascular diseases. Recent introduction of biplane probes has enhanced the diagnostic capability of this imaging technique. This article discusses the technique of biplane transesophageal echocardiographic examination and image orientation. The diagnostic value and advantages of various biplane transesophageal images of the heart, aorta, and aortic arch from various esophageal positions are described.

We describe two patients with blue digit syndrome in whom transesophageal echocardiography was able to identify mobile thrombotic masses attached to the irregular intimal surface of the descending thoracic aorta. These patients were treated with heparin and warfarin and did not have recurrent episodes of peripheral arterial embolization. In this article we discuss the diagnostic and therapeutic approaches in patients with peripheral arterial embolization and blue digit syndrome.

Rupture of the aortic sinus of Valsalva into the right ventricle is a rare complication of bacterial endocarditis. The majority of previous cases have been reported in patients with aortic valve endocarditis. This report describes this complication in association with infective endocarditis of a congenital membranous ventricular septal defect. Color flow imaging showed a mosaic-colored continuous flow signal from the right aortic sinus to the right ventricle. Continuous wave Doppler interrogation showed high-velocity systolic and diastolic flow signals due to continuous left-to-right shunt from the aorta to the right ventricle. The left-to-right shunt through a restrictive membranous ventricle septal defect was visualized as a mosaic-colored high-velocity systolic flow signal. These echocardiographic-Doppler findings permitted surgical correction of these defects without cardiac catheterization.

Infective endocarditis continues to be a significant diagnostic and therapeutic problem. During the last two decades, transthoracic echocardiography, and more recently, transesophageal echocardiography have been used in patients with the clinical syndrome of endocarditis to detect vegetations and assess the extent of valvular damage. Certain echocardiographic findings have important prognostic implications and can help determine the timing of surgical intervention. This paper will review the role of echocardiography in the evaluation and management of patients with infective endocarditis.

A patient with recent inferior myocardial infarction with right ventricular involvement developed severe hypoxemia unresponsive to 100% oxygen. Contrast two-dimensional echocardiography revealed right to left shunting through an aneurysmal fossa ovalis with a patent foramen ovale. This was confirmed by cardiac catheterization. Surgical closure of the defect was probably life-saving. This case report illustrates that right to left shunting through a foramen ovale should be considered in the differential diagnosis of hypoxemia in patients presenting with inferior myocardial infarction.

Erythrocyte selenium dependent glutathione peroxidase (GSH‐Px) activity and plasma vitamin E levels were measured in 20 psoriatics. Psoriatics had significantly lower GSH‐Px and plasma vitamin E levels than did controls. Psoriatics were divided into three grades by the rule of nine: Grade I—less than 33% skin involvement, Grade II—33‐66%, and Grade III—over 66% skin involvement. Grade III psoriatics showed much lower values of GSH‐Px and plasma vitamin E, showing a definite correlation with the percentage of surface area involved.

Hypertrophic cardiomyopathy is a primary myocardial disease that is characterized by a hypertrophied and nondilated left ventricle. Echocardiography has proved to be a valuable noninvasive tool in the diagnosis, follow-up, assessment of therapy, and family study of hypertrophic cardiomyopathy. A complete M-mode, 2D, and Doppler examination should be performed to define the structural, functional, and flow abnormalities in this condition.

This study was designed to define the frequency and explanation of false negative diagnosis of aortic dissection by aortography and transesophageal echocardiography.

Infection of the mitral-aortic intervalvular fibrosa occurs most commonly in association with infective endocarditis of the aortic valve. Infection of the aortic valve results in a regurgitant jet that presumably strikes this subaortic inter-annular zone of fibrous tissue and produces a secondary site of infection. Infection of this interannular zone then leads to the formation of subaortic abscess or pseudoaneurysm of the left ventricular outflow tract. This infected zone of mitral-aortic intervalvular fibrosa or subaortic aneurysm can subsequently rupture into the left atrium with systolic ejection of blood from the left ventricular outflow tract to the left atrium.

The phenomenon of isolated mechanical alternans of the right ventricle is described in the setting of right ventricular infarction. We also discuss the resemblance of right ventricular infarction to cardiac tamponade or pericardial constriction.

•Present an overview of the grid-connected sustainable energy system for the urban sector.•Evaluate worldwide energy scenarios and the adding value of renewable energy resources.•Analyse different opportunities of implementing distributed energy resources, PV system and energy storage system, for an optimal dynamic behaviour scheme.•Detail the future perspective of using distributed energy resources connected to the utility grid based on the smart grid environment.

A 31-year-old man with a history of intravenous drug abuse and tooth abscess was admitted for evaluation of possible infective endocarditis. Echocardiography showed that he had a left atrial mass. The mass removed from the left atrium had the same histology as the primary embryonal carcinoma discovered in the right testicle during hospitalization. The patient made a smooth recovery after surgical intervention and chemotherapy. This is believed to be the first reported case of metastasis from embryonal carcinoma of the testis to the left side of the heart that was successfully removed at surgery.

Kidney or liver involvement in syphilis is quite rare. The patient described here had both nephrotic syndrome and granulomatous hepatitis during secondary syphilis. REPORT OF A CASE A 29-year-old man was admitted to the Brooklyn Veterans Administration Hospital on Jan 26,1976 with a two-week history of fever, night sweats, and nonpruritic rash, and a two-day history of pedal edema.Physical examination showed a comfortable young man with normal vital signs. There were papulosquamous lesions on the abdomen, elbows, and penis, generalized lymphadenopathy, and hepatosplenomegaly.The WBC count was 7,000/cu mm. The VDRL was positive at 1:256. The fluorescent treponemal antibody-absorption test was positive. Results of urinalysis showed 4+ proteinuria, without casts or hematuria. Results of laboratory studies disclosed the following values: 24-hour urine protein, 5.7 g/dl; serum protein, 5.7 g/dl; albumin, 2.3 g/dl; cholesterol, 238 mg/dl; and alkaline phosphatase, 323 μU/ml. Results of the following tests were within normal limits:

Pathoanatomic disorders of venous occlusion were well documented in certain human organs. In order to investigate if coronary vein occlusion may alter myocardial structure or contractility, we experimentally ligated the coronary sinus in seven anesthetized, open-chest goat preparations. Left ventricular wall motion and wall thickness was recorded by two-dimensional echocardiography on each goat before and within two hours after the coronary vein ligations.