mohammad tabrizian

Today, the use of integrated (hybrid) energy supply systems due to the reduction of electrical and thermal losses, better control of distributed generation sources to better feed the system loads, reduce the emission of environmental pollutants and increase the reliability of load supply even in the event of failure , Is on the rise. In this research, an optimal and economical method to design a hybrid energy supply system based on CHP sources and photovoltaic sources to combined heat and power required by consumers, taking into account various costs such as initial investment cost, operating cost, Fuel costs, maintenance costs and various technical constraints such as production limitations of each source, power exchange with the upstream network and maintaining power balance are presented. Inheritance (genetic) algorithm has been used to solve the resulting optimization problem due to its good ability to solve complex problems with a large number of variables. The results show that in designing the system to supply electricity and heat, the system connected to the grid requires lower operating costs than the other two modes and the possibility of exchanging power with the upstream network due to the purchase of electrical power required from The network significantly reduces system costs in the event of a shortage of photovoltaic panels and the sale of power to the grid during off-peak hours and overproduction, as well as during peak hours of the upstream grid, where electricity prices are higher.

Existing power grids are inefficient, due to the lack of energy management and the lack of storage, so power plants have to produce more to maintain power quality. But by using network savers, the need to build more power plants is reduced and network stability is improved and many of these inefficiencies will be remedied. By launching this market, consumers are encouraged to optimally manage their consumption, sell power to the grid during peak hours, increase network stability, and compensate grid shortages through the nearest storage network operator due to proximity to the storage. Consumers cause the least transmission line losses. In this paper, using the proposed multi-objective fuzzy multi-objective optimization problem for modeling of energy storage systems (ESS) planning in active distribution networks (ADS) considers the impact of ESS optimization strategy. Finally, the modified IEEE standard 33-bus distribution system will be used to evaluate the feasibility and performance of the proposed model by examining the two hybrid algorithms.

Finding the best situation for the expected profit by each of the participants (players) in the secondary auction market of financial congestion transmission rights.

From the point of view of game theory, finding at least one Nash equilibrium point for this competition takes into account the various constraints of the secondary auction market.

This paper study the issue of financial transmission congestion contracts then uses the game theory to analyze the short-term (weekly) secondary FTR markets, in which the players manage the transmission risk through optimal biddings.

Originality/Value: 

Congestion risk management is one of the most important topics of transmission network management in restructured power systems and electricity markets in the world, especially markets based on regional or local pricing, whose main tool is transmission financial contracts. In the other scientific articles published so far, mainly the modeling and analysis of the primary auction markets of transission congestion financial rights have been discussed, and the secondary auction markets of these contracts, which have a different pattern, have not been scientifically analyzed. The main innovation of this article is to pay attention to this issue using application of game theory.

Electricity transmission lines in the unstable state have problems such as the increased voltage at the end of the line and loss of stability, and in pregnancy, problems such as voltage drop and loss of transmissible capacity, and in some cases of voltage instability, include transient power fluctuations and instability due to disturbances. These problems are exacerbated by the increase in the length of transmission lines. To solve these problems, the active and reactive voltages and capacities must be controlled momently to reduce line losses and increase power transmission capacity as well as improve reliability and maintain voltage stability the use of FACTS equipment is now expand worldwide and can be studied and proposed for the prospects of Iran's national grid. In this article, a more complete model based on weighted and ranked of different possible events simultaneously and optimally locating two examples of these devices including Thyristor Controlled Series Compensator (TCSC) and Static Reactive Power Compensator (SVC) to improve Available Transfer Capability (ATC) is proposed in 14-bus and 24-bus power networks by the IWO (Invasive Weed Optimization) method and then its results will be compared and evaluated with other optimization methods.

Today, electric vehicles have been significantly considered due to the lack of air pollution. However, due to the large volume of vehicles in the city, connecting them to the distribution network without a control program may cause congestion in the network lines and substations. Therefore, a bi-level hierarchical method for connecting electric vehicles to the distribution network to coordinate services and performance constraints of the three main elements, namely fleet operator, distribution system operator, and capacity market operator in the presence of vehicle owners and taking into account driving requirements, charging and compaction costs of power lines and transformers are recommended. In this method, first car owners and fleet operators present their charging program to the distribution system operator according to the predicted market prices. In the next step, if this charging program leads to congestion in the lines or substations and power transformers, it is returned to the fleet operators and the shadow price is determined by the capacity market operator based on the congestion status. Then the new charging program is dispatch according to the new market prices. The proposed method is implemented in a sample distribution network and the simulation results show the efficiency of the proposed method.

This article, proposed a method to coordinated utilization of gas-electricity integrated distribution system, including CCHP systems and renewable energy sources, considering AC load flow analysis in an electric grid and the calculation of gas consumption in a gas grid. In this research as you will see, an effective method proposed to prevent transmitting of power generation swings of renewable sources over trans-regional power line and maximum utilization of renewable sources. The proposed model tested on a modified distribution power grid IEEE 33 and 24-node-gas grid. Results show that total expense of adjustment in Conventional design will rise dramatically by increasing of unit. While in the presented design, adjustment expense will remain stable and increase slightly.

Congestion Risk Management is one of the most important subjects of Transmission management in deregulated power system and world electricity market, especially markets of zonal or local pricing in which Firm Transmission Rights (in other words Financial Transmission Rights) are the main elements. In this study, considering subjects of Financial Rights of Transmission Congestion, methods of optimum proposal of different Rights by participants of transmission rights second auction of electricity Market in short period (weekly) for Congestion Risk Management will analyzed. At the end, a proposed method in a typical network is tested and the numerical right values shown.

This paper investigates smart home energy management in consideration of tradeoffs between residential privacy and energy costs. A multi-objective approach that minimizes energy costs and maximizes privacy protection is proposed. This approach leads to a multi-objective optimization problem in which the two objectives addressed in separate dimensions. PSO algorithm that employs a stochastic search used for power scheduling of home appliances and uses deterministic battery control developed accordingly. The proposed approach can avoid some drawbacks faced by conventional weighted-sum methods for multi-objective optimization. Simulations reveal that the proposed approach can maintain a reasonable energy cost while robustly preserving user privacy at a sensible level, finally the numerical results shown and analyzed.