Journal of Energy Management and Technology
Volume:3 Issue: 4, Autumn 2019

In this paper, two control strategies are proposed for distributed generation inverter (DGI) to control 1) active power exchange with the grid, 2) load voltage and 3) grid current. The main goal in these strategies is supplying of local load with a standard sinusoidal voltage in the presence of grid voltage distortions and load current nonlinearity. In conventional DGIs, the load is directly and without intermediate impedance connected to the grid, thus, the possibility of load feeding with appropriate voltage quality is hindered in the grid connected mode. In order to overcome this deficiency, DGI with a LC-L filter topology and two control strategies are presented in this paper to supply local load with standard voltage and exchanging power with the grid, simultaneously. In the first control strategy, local load is supplied with pure sinusoidal voltage and grid current quality is not important. In the second control strategy, load voltage waveform and grid current waveform are controlled with adding appropriate harmonics to load voltage. For the implementation of the mentioned controlling strategies a cascade power-voltage-current control structure has been proposed. A new controller has been introduced in the stationary reference frame for the voltage loop which gives the opportunity for compensation and tracking of harmonics without the need for complex and vast calculations. Test results under nonlinear load and non-ideal grid conditions validate that the proposed method can supply local load with standard voltage, inject power to grid and also control of grid current.

By development of industries, excessive consumption of the fossil fuels is becoming the worldwide crisis in the years ahead. Besides the proper thermal and power performance, the compression ignition engines make lower greenhouse-gas emissions compared to the spark-ignition engines. Using dimethyl-ether (DME) as an environmentally friendly fuel in a diesel engine can improve its advantages. In the present paper, the effects of the piston bowl geometry in a DME-burning direct injection (DI) engine have been numerically evaluated. In order to enhance combustion and emission characteristics, various piston bowls with different bowl volumes are designed and examined. Furthermore, the influences of engine speed and compression ratio are further investigated. The results showed that lower bowl volume led to more air-fuel mixing. Reduction of the bowl volume size from 6.446e-005 m3 to 1.5282e-005 m3 caused reduction in emissions of the soot, NO and CO by 91%, 9.3%, and 99%, respectively (the exhaust CO2 concentration was almost identical for each piston bowls). in addition, lower compression ratio caused reduction in temperature and NO emissions. It is determined that amount of exhaust emissions is affected by increasing the engine speed, and mean pressure of the engine cylinder reduced, dramatically. It is found that taking advantage of DME fuel in the ISM 370 diesel engine caused reduction in the NO, soot, CO and CO2 by 75%, 20%, 8%, and 44.43%, respectively, under 1200 rpm engine speed.

Parametric evaluation and thermodynamics first-law examination of a novel multigeneration system, which is comprised of a hybrid solid oxide fuel cell/gas turbine (SOFC/GT) system, a heat recovery heat exchanger, an ERC (ejector refrigeration cycle), and a PEM (proton exchange membrane) electrolyzer, is conducted. The proposed multigeneration set-up produces refrigeration output, electricity output, heating output, and hydrogen, simultaneously. An exhaustive analytical evaluation of the introduced system is presented and findings are testified by accessible data. The findings showed that the introduced set-up yields heating load, refrigeration load, net electricity, and H2 rate of 277 kW, 84.42 kW, 184.2 kW, and 1.433 kg/h, correspondingly. Under this circumstance, the overall energetic efficiency of the integrated system was calculated around 79.5%. In addition, a thoroughgoing parametric examination for the reckoned set-up is revealed on the basis of central factors. It is reckoned that the energetic efficiency is aggrandized at relatively high SOFC current densities, SOFC inlet temperatures, gas turbine outlet pressures, pinch point temperature differences of heat exchanger 5, ejector primary fluid pressures, and evaporating temperatures or at low compressor pressure ratios and condensing temperatures. Further, the results indicated that the introduced system’s performance may be maximized regarding the SOFC inlet temperature into account.

One of the main concerns of today's world is energy; therefore, a mission for experts is to try to optimize energy consumption and to make sustainable development happen. The subject of the current study is the relationship between the today common architecture of Tehran's luxury buildings as quasi -neoclassical buildings with sustainable architectural goals. Therefore, in order to investigate the neoclassical views of the unrestricted statistical population in this research, neoclassical-style buildings of Tehran's region 1 have been selected.The sampling method for this research is a probabilistic one. For this purpose, 5 out of 10 areas in Tehran’s region 1 were selected randomly and sample size was determined according to the assumptions of the research statistical model and the sampling size determination formula. In this regard, three buildings with a quasi-neoclassical facade were randomly selected from each area. As the samples were selected, the principles of sustainable architecture were identified and a table was provided for the buildings whereas each principle held 5 scores. On this basis, each of the pseudo-neoclassical buildings each building was scored according to sustainable architecture and finally all of the buildings were analyzed by description and results were driven.The present research leads to finding answering to the following questions:1. Do the prevailing quasi-neoclassical buildings in Tehran conform to the principles of sustainable architecture?2. Does the prevailing architecture of northern parts of Tehran match the energy conservation laws?

Nowadays, the prediction of the load performances in the smart systems is necessary to generate the minimum energy. In a smart home, there are various appliances that each of them has different behavior. These differences defined as appliance states. In this paper, an effective hybrid method is proposed for load disaggregation of appliances. Factorial Hidden Markov Model (FHMM) with high accuracy is used for appliances states modeling. In this model, the present state of each appliance is available, and then the defined allowable states for the next instant are provided. For optimal estimation of states, the Particle Swarm Optimization (PSO) algorithm is employed. Furthermore, three constraints are applied in PSO to modify the states matrix; first, every appliance must has one state at any instant; second, considering of the appliances that always is active; and last, using of FHMM for load models production. In the last constraint, by using FHMM, counts of the estimated databases as well as the calculation time are remarkably reduced. In order to show the effectiveness of the proposed method, speed and accuracy of the responses for practical data of six smart homes are compared with other methods.

ABSTRACT This paper addresses a multi-objective approach for simultaneous dynamic expansion planning of conventional sub-transmission grid and Regional Virtual Power Plant (RVPP). In such a feed-in tariff electricity market, it will assist RVVP’s stakeholders in deciding whether or not they should invest in new equipment’s installation. A Multi-Objective Particle Swarm Optimization (MOPSO) algorithm as a heuristic optimization method is proposed to eliminate the conventional centralized planning, which has led to competition between Regional Electric Company (REC) and RVPP for power delivery in sub-transmission system. Two objective functions are considered for simultaneous expansion planning of these two systems. The first one takes the minimum cost of the REC, as the sub-transmission grid operator, into account while the other one considers profit maximization for RVPP. To achieve the goals, MOPSO algorithm is employed to find the best expansion of REC and best location and capacity of RVPP’s resources. Having solved the proposed multi-objective optimization problem, a Pareto front is determined to show the trade-off between REC and RVPPs' contributions in joint optimal expansion planning of conventional sub-transmission grid and the RVPP. To demonstrate the applicability and effectiveness of the proposed approach, a realistic sub-transmission system in Guilan Province, Iran is used as a test system, and the results are evaluated accordingly.

In Iran, due to low electricity price, the development of electrical energy storage systems (EESS) is not economic, currently. This paper presents new economic indicators based on the value of EESS in the electricity network. The economic value of the battery is tested for three different applications: capacity benefit, avoidance of carbon emitting and loss reduction. In doing so, a comprehensive economic analysis is performed to explore the real benefit of the spreading EESS. In addition, a new economic term, opportunity cost, is established to show the importance of EESS which is calculated by comparison levelized value of energy (LVOE) and levelized cost of energy (LCOE). The proposed model is applied to investigate the techno-economic analysis in the electricity grid of Kerman, Iran. Such analysis introduces the importance of EESS in investment from national and regional electricity network viewpoints. These results also show that at the current retail rate, the EESS developing is not beneficial but from the viewpoint of national saving, the EESS developing is very attractive. In all scenarios, the LVOE of the battery is more than its LCOE. It can be shown that via the proposed economic platform of EESS, the efficiency in the electricity network could be increased by reducing losses and capacity requirements.