محمدصادق قاضی زاده

To improve the resiliency of the distribution system during normal and emergency conditions, approaches for planning and operating are required so that the network can supply more loads during normal and emergency times. Thus, with the cellular approach in network planning, according to the production and consumption, the cellularization of the network to supply more loads can be considered. Consequently, the identification of energy cells and the boundary of energy cells is a challenge in the planning issue. This article achieves and identifies the maximum number of energy cells and the border among energy cells of distribution systems. The proposed objective functions for solving the resilience problem include the number of supplied loads and the number of unsupplied loads in normal or abnormal conditions. Furthermore, the eigenvalues and eigenvectors of the Graph Laplacian matrix of the distribution network are used to identify the maximum number of cells in the distribution network and the boundary among the generated cells, considering the prediction of distributed generation and consumption load based on fuzzy modeling. To show the efficiency of the proposed method, the test systems of 69 and 118 buses have been simulated. The results prove the proper performance of the proposed method.

The fuel cells are electrochemical equipment that produces electricity by compounding hydrogen and oxygen in a specific membrane. Fuel cells, as a cutting-edge technology and a maintenance free energy conversion equipment, have the potential to play a significant role in generation of clean electricity, especially for home size CHP and clean transportation based on hydrogen fueled vehicles, can provide new opportunities in the world’s economy. In a study for the financial evaluation of the establishment of a fuel cell production facility in Iran, with a capacity of one million units per year, the economic modeling has been done by COMFAR software based on the UNIDO’s Instructions. According to the results of this evaluation, IRR was well beyond the discount rate and the normal payback period as well as the dynamic payback period were in the range of 4-5 years. All of the financial ratios and risk analysis in the six stages justified the bill of investing.

Developing countries like Iran face increasing energy demands due to population growth and economic expansion. The country has numerous renewable energy resources that account for the majority of its total energy supply. As fossil fuel resources are running out, the government plans to increase its renewable energy share. Many studies have already been conducted on renewable resources. However, the interdependence between the criteria used to evaluate renewable resources has not been considered. This paper presents a planning, decision-making, and policy framework for renewable energy based on the Analytical Network Process (ANP). ANP is a multi-criteria analysis method and provides a tool for determining the relative importance of all criteria that affect the decision objective. This process allows us to identify dependencies and include them in the multi-criteria evaluation and decision-making method from the point of view of a group of experts and professionals on the subject. The case study of this research is related to the country of Iran, and strategic criteria such as technology, economy, environmental, political and social impacts are calculated and priorities for renewable energy are set and analyzed. The results of this study show that solar energy is at the top of energy alternatives for the country. Such studies help countries to make the best use of their renewable energy sources

In this paper, to implement the reconfiguration of the intelligent distribution network and sizing the distributed generations (DGs), simultaneously, a stochastic multi-objective framework is presented in which the goals of reducing the energy losses, operating costs and emissions of environmental pollutants are followed. In most of the researches carried out for the network reconfiguration, the customer and distribution substation loads have been assumed to be fixed, while in reality these loads are changing. Generally, in the power system planning, the worst case which is the maximum possible load is considered, but the obtained configuration with this assumption is certainly not the optimal configuration. Therefore, in this paper, in order to cover the uncertainties associated with the load, the framework for the reconfiguration and DGs sizing problem is presented as a chance constrained programming problem and the Monte Carlo simulation is used in it. The problem of reconfiguration and DGs sizing at the same time in order to achieve predetermined goals is a multi-objective optimization problem. In order to solve it, this paper uses a newly introduced powerful optimization method called human-behavior based optimization approach. Finally, the proposed stochastic multi-objective framework is implemented on an IEEE 33-bus network, and the results are analyzed.

This paper proposes a mathematical model for the short-term security constrained operation problem in a radial Microgrid. The conventional security modeling in the transmission system is not appropriate for radial networks, where, a line outage creates an island and usually leads to the load shedding. This paper proposes a security model for the radial Microgrid using the consumers’ damage indices. In addition, it analyses the load control effects. It includes these contingency state constraints in the short-term scheduling: power balance in the island, allowed frequency deviation range, island’s capability to continue the service and load sensitivity to the duration of the abnormal condition. Hourly scheduling of the resources, loads and power exchange with the main grid is performed with the aim of minimizing the load damage in the contingency states and maximizing the profit at this selected security level. The proposed model is applied to IEEE 123-bus test system.  It reduces the load damage index at least 38% in comparison to the other operational strategies. The cost-benefit assessment is performed to analyze the proposed method in different viewpoints.

This paper presents a mixed integer linear program (MILP) model as well as a solution method based on the Benders decomposition algorithm for optimal design of sustainable Energy Hub (EH). A modeling framework to consider environmental (Env) and social (Soc) impacts of the EH's components is incorporated to achieve sustainable EH. First, the life cycles of different components are analyzed in order to determine Env and Soc impacts. Then, the EH design model is developed by using scenarios-based stochastic programming integrating Conditional Value-at-Risk (CVaR) in its objective function as a risk criterion to deal with uncertain nature of parameters. Benders decomposition (BD) algorithm is used to decompose the original problem in order to address heavy computational burden of the problem, especially when a large number of scenarios is used to properly represent uncertainties. The results shows effectiveness of the proposed BD to handle large problem sizes compared to the CPLEX solver and indicates that taking the external cost into account resulted in higher renewable Distributed Energy Resources (DERs) in the optimal configuration, which have lower negative Env and Soc impacts. Also, strength of stochastic programming in handling data uncertainty and controlling risk level is investigated.

The aim of this paper is to provide a comparison between different methods of natural monopoly regulation for electricity distribution companies in Iran and introduce the best suitable one based on productivity, quality and incentive considerations. Here we have concluded that the price cap regulation model is the most efficient method of regulation for the situation under consideration. Based on the literature, the target values of both productivity and quality has been calculated in different scenarios of this research. The sample consists of 39 electricity distribution companies in Iran during period 2006 to 2016. First, using the SFA and DEA methods to determine the efficiency score of each company, we have calculated the X-factor for every firm in a 5-year period. In addition, the X-factor was calculated based on Malmquist index and differential method. The results suggest that target X-factor is in the range of 1.7% to 3%. The results indicated that there is an opportunity to increase productivity of electricity distribution companies. To encourage the firms to improve their productivity, a higher target rate of productivity growth would be considered for low-efficiency firms and a lower target for high-efficiency ones. Service quality has been evaluated mainly by quantification and measurement of energy not supplied (ENS) and the waiting time for a new customer to be connected to the power grid and to be able to use electricity. And the target quality value was set for each company.

The issue of protecting the environment and preventing environmental pollution is one of the priorities of Iran’s economic and social development plans. The purpose of this paper is to analyze changes in the environmental effects of electricity generation, as electricity production patterns change, on production and welfare of households in Iran by using the social accounting matrix of 2011 and a computable general equilibrium model based on that framework. We evaluate four different policy scenarios based on the monetary value of the negative environmental effects of electricity generation.  The results indicate that application of electricity generation’s negative externalities has a positive effect on economic growth and a negative effect on household welfare. Secondly, with the current structure of electricity generation, the application of external costs of electricity production will increase economic growth by 0.0576 to 0.0736 percent and will reduce household’s welfare by -1.955 to -7.171 percent. Thirdly, by changing the pattern of electricity generation in Iran and moving towards clean electricity production and reducing electricity production from fossil fuels, the effect of electricity generation externalities on economic growth and welfare will be reduced. According to the research results, if the share of electricity production from fossil fuels is reduced to 85%, the economic growth and welfare of the household will respectively vary from 0.0553 to 0.0727 percent and from -1.733 to -6.363 percent.

Electricity is one of the most important infrastructure of the country. After the successful experience of industrialized countries for separate different parts and privatization in electricity industry, Iran since 1382 has begun to privatize the electricity industry. The electricity distribution sector is natural monopoly and, according to economic theory must operate under regulation for quantity of supply, price and quality to protect social welfare. There are various methods for regulation such as rate of return and incentive regulation, in many of these methods foucus on efficiency and productivity of firms. But the conventional static efficiency methods mainly reflecting short-run performance, and only show a close view of the long-run equilibrium path. When componis investment, the behavior of short-term factors that affecting the company may not be adjusted immediately, so short-run inefficiency will be transferred to subsequent periods. This effect caused by the the adjustment costs of capital and production capacity and in short run reduce efficiency in firms and should be considered in the regulation. In this paper, the dynamic efficiency of 39 electricity distribution companies during the period 2009-2015 was calculated using distance function. To estimate the the posterior distribution of model parameters, the simulation based on Markov chain Monte Carlo (MCMC) was used. The results show that environmental factors affect the efficiency in firms. The industry average efficiency increased from 67% to 70% and consistency for inefficiency was 92% during the period.

Utilization of power electronic interface in end-user appliances adds many newfound features to these devices. Cooperation in Volt Ampere Reactive (VAR) supply is one of these new capabilities and enables these devices to act as Distributed Energy Resources for reactive power injection and absorption. Proper integration of these power electronic interface capabilities into traditional utility system operations, it can be used as beneficial tools for distribution management and voltage profile enhancement. Regarding the present situation in distribution system, it is not practical to control all DERs centrally. Therefore, in this article, two proposed central control method and droop control were considered. The Multi-Criteria Decision Making (MCDM) technique with fuzzy theory was used to prioritize the candidate buses for their participation in Volt-VAR program. The contribution of the pre-mentioned active DERs in reactive power compensation was evaluated in this study

Environmental problems are one of the most challenging issues for the entire world and each country. In economic studies, environmental issues are analyzed as negative externalities. In this article, the negative externalities of electricity production on the output growth of different sectors and household’s welfare in Iran’s economy have been studied through price system using Computable General Equilibrium (CGE) model empirically. In this regard, Iran’s Social Accounting Matrix of 2011 and GAMS software by introducing five scenarios related to environmental effects of electricity production have been used. The results show that firstly, the internalization of electricity production externalities reduces the output of agriculture and industry sectors in all scenarios, while the output of services will increase. Secondly, internalization of electricity production externalities increases total economy’s output and declines the household’s welfare.

After the restructuring and privatization of the electricity industry, the main purpose of the DISCOs is to increase their income, according to the existing laws. The existence of private distributed generation (DG) units in the distribution network and the possibility to buy additional electricity of DG with a less price than the wholesale market, capacitor installation, payment of energy not supplied to customers, the cost of energy losses and voltage drop problem in the distribution network, has created opportunities and challenges for DISCOs that are looking for adopting a suitable strategy for higher profits. In this paper, as the first scenario, it is depicted that when there is no DG unit in the network the increasing in the DISCO’s income is achievable by optimal allocation of both fixed and switched capacitors. In the second scenario, this is done by determination of the maximum acceptable DG energy sourced electricity purchasing price with a known location, and in the third one, by determination of the purchase price from the DG while the locating has been done by the DISCO. Simulation studies are done on a 20kV 18-bus distribution network in Rasht city, and the results are presented at the end.

It is essential to consider electric energy storage systems in power system studies due to increasing utilization of these energy resources. In this paper we augment the generation maintenance scheduling problem to consider effects of energy storage systems. In the new formulation the outage schedules of generation units and energy storage systems are determined jointly. The problem is modeled in such a way that the main effect of energy storage systems, -which is switching between charge and discharge mode to comply with power system requirements- is considered. The model is formulated as a mixed integer linear programming problem and is implemented in test systems. The results show the capability of the proposed model in joint maintenance scheduling of generation units and energy storage systems.

Restructuring in electrical power distribution utilities, energy loss management is one of the critical activities to enhance network efficiency. Accordingly, monitoring of technical loss and strategic planning for loss reduction would be a main target of asset manager. For loss monitoring, the usual methods of loss calculation and estimation need numerous data which is not used mostly to utilize real networks. In this research, a practical method for loss monitoring is introduced according to the viewpoint of components’ supply chain to network. For this purpose, indictors are extracted by the focus group for each process of component inserting and their probability distribution functions are calculated. Then, permissible values of indicators are determined by the Delphi method and to calculate new probability functions, the probability distance of each process is calculated. Finally, a real distribution network with historical data is used here to study the proposed method. The results illustrate that the most deviation is in the design process from the power loss viewpoint.

One of the major challenges for power system operators and administrators who are involved with the electricity market, reduce the uncertainty of wind power in a competitive market. In this study an integrated partnership model wind and pumped storage power plants in the energy and reserve market clearing Different aspects of the operating costs compared. Also, the role of pumped storage plants as storage for the increased penetration of wind power in the power network has been compiled. In addition, reduced operating costs, reducing the need to store the rotating and nonrotating joint exploitation of wind and storage are discussed. To simplicity of the problem, Three-bus system, the presence of a pumped storage unit and an wind unit during the simulation period of 4 hours is considered.

The presence of new generation of electrical loads equipped with power factor correction devices makes it possible to utilize end-consumers in distribution grids voltage improvement. In this paper, reactive power and voltage control of a smart distribution grid by using end-consumers are studied. The distributed control algorithm is used as a suitable mechanism with less computational burden. In this regard, through the ε-decomposition approach the distribution network is divided into some subnetworks. After that, candidate buses for reactive power are selected and optimal reactive power injections at each candidate bus are acquired by genetic algorithm. Also, the impact of constant voltage distributed generations on voltage control is investigated. Finally, in order to evaluate effectiveness of proposed framework, IEEE 33-bus and 69-bus test systems are used. Simulation results show significant impact of proposed framework on voltage improvement of the distribution network.

Iran is flaring about 30 million cubic meters of associated gas per day in onshore oil fields. Suboptimality of economic extraction and production of exhaustible natural resources pawn the national benefits. Therefore, the main purpose of this paper is analyising the economic and technical feasibility aspects of reusing flared associated gas based on Capital Asset Pricing Model (CAPM). In this study time series data of average associated flared gas from 44 Iranian onshore oil fields has been employed. Additionally, three investment scenarios mean gas injection to the oil fields, electricity production and final consumption have been considered. Results of this study show that such oil fields produce less than 3 million cubic meters associated gas per day, gas injection to oil fields is the optimum alternative whereas using of associated gas to electricity generation is advised for other scenario.

Information about network components is of great importance for asset management decision making. This information is needed as input for the asset management decision process to come to a decision. To be able to extract the requested information، analysis and evaluation are needed. On the other hand، for efficient and economical asset management from reliability view point، analysis of failure rate for determination of origin of fault in component is an important task for asset manager. The failure rate of components is obtained by gathering data in outage management process that is available usually in detail in outage databases in electrical distribution. In this paper، failure analysis of process is obtained by assessment of process of component entry in distribution system. In this analysis، failure factors and sub-factors of each process is assigned by focus group and then relation between factors and causes of component failure is obtained by Delphi method. Finally، reasons of process-based failure are invested by modeling of failure rate for each process.

According to the latest developments in smart grid infrastructures of today’s modern networks, in this paper, end-consumers are presented as a means for participating in distribution networks voltage control. In this regard, for reactive power control of the smart grids, a distributed control approach is proposed as an efficient approach which improves computation burden of the problem, considerably. In the proposed approach, at first, epsilon-decomposition technique is adopted to calculate sensitivities of bus voltage to the injected reactive power. Therefore, buses with strong voltage relation are considered as a region which divides the network to some voltage related regions. Afterwards, candidate buses for reactive power injection are identified for each one of the achieved region. It is noted that, candidate buses of the network are those with reasonably better response to the reactive power injection. Finally, genetic algorithm is applied to obtain optimal reactive power injection of each region. For better evaluation of the proposed distributed reactive power control model, the IEEE 33-bus test system which is commonly used in literature is applied here. Simulation results clearly illustrate the effectiveness of proposed voltage control framework in improving voltage profile of distribution networks.

One of the most important ways that conserve fossil fuels is the use of renewable resources. Biogas is one of the most important renewable resources. Biogas is created from anaerobic fermentation of livestock waste in a fermentation chamber. Biogas technology is an important from several aspects; First، the significant social impact of this technology in the field of environment and human health. Second، it can be fired using biogas generators for generate electricity and third، sludge biogas unit output، would be a rich fertilizer that can greatly increase the efficiency of agricultural products. This paper delivers a cost-benefit analysis of biogas-fired plants، from the perspective of the private sector and the public sector، of the dairy industry in Iran. The results of both analyzes indicate high economic efficiency in the different sizes of biogas-fired power plants in Iran dairy industry.

Due to growing demand of the electric energy, the need to generation expansion planning is inevitable. In this paper at first effective criteria in Generation Expansion Planning (GEP) are determined and a novel approach for GEP is proposed. In this approach Fuzzy-Analytical Hierarchy Process (FAHP) is utilized for GEP. The Fuzzy is one of the techniques that uses for weight assessment in decision making in Multi Criteria Decision Making (MCDM) model. For this purpose, five criteria are introduced and then by utilization of the FAHP, the optimization of GEP problem is implemented. In the first stage, the Local Marginal Price (LMP) of each bus is calculated by Optimal Power Flow (OPF) execution. In the next stage, base on the criteria that will describe, the candidate places for power plants installation are determined. Finally, the FAHP is used to assign a value to each criterion and by using these values the optimal place for installation of power plant among the candidate places is determined. The IEEE 14 bus network is used to simulate and evaluate the effectiveness of the proposed method.

Concept of Virtual Power Plant (VPP) can be used to aggregate Distributed Energy Resources (DER) units into restructured power systems. This paper presents an optimization model that provides optimal operating strategy and benefit maximization scheme as well as the reduction of the emission for a VPP. The VPP considered in this paper consists of a wind turbine, a CHP system, several DGs, and loads with curtailment options. VPP can be participated in wholesale power market as an entity with dual role including producer and consumer. The presented model is a nonlinear mixed-integer programming problem with constraints. In this problem, Objective function is VPP profit with aim supply both thermal and electrical energy demands. The results demonstrate the efficiency of the proposed approach to satisfy the demand and to reduce emissions.

Demand Side Management (DSM) is one of the most important methods that is used to maximize the benefits of electric power market participants. Demand Response (DR) are methods from DSM that can be defined as the changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time. This paper is focused on simultaneous implementation of security constraint unit commitment (SCUC) and Emergency Demand Response Program (EDRP) by using economic model. Considering that the simultaneous implementation of SCUC and EDRP is complex non-linear optimization problem with continuous and discrete variables، this paper is used linearization method to linearized the non-linear terms and then Mixed Integer Linear Programing (MILP) is used to solve the optimization problem. The software GAMS 23. 6 has been used for this work which is fast and robust software for solving various types of optimization problems. The IEEE RTS 24 bus test system is used to simulate and evaluate the effectiveness of the proposed method.

Demand response is becoming a promising subject in operation of restructured power systems. As a result, recently more attention is paid to demand response programs. Customers can contribute in operation of power systems by deployment demand response. The growth of customers’ participation in such programs may affect planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Then, avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. In addition, changes in investment cost and total cost paid by customers are investigated. The effects of demand responsiveness are studied from both the customers’ and generation companies (Gencos) points of view. The proposed model has been applied to modified IEEE 30-bus system and the results are discussed.

Attention has been paid to the Demand Response (DR) programs in recent years to improve the power system operation. Demand Response affects market clearing price، which is the main motivation for investment، and thus the trend of investment on generation expansion will be affected. So far، the demand has been considered inelastic for modeling the investment on generation expansion. However، increasing the deployment of smart grid has waived this assumption. In this paper، we have used stochastic dynamic programming for modeling the generation expansion problem. We have considered both the renewable resources and demand response in modeling. In the proposed model، the uncertainty in generation and the accuracy of the price responsive demand performance are considered. In this regard، the market clearing price is determined by interaction between price and the price responsive demand. Some long-term indices are proposed and using the simulation results، they are evaluated. The achieved results، quantitatively confirm that the demand response results in decreasing the price and the outages and therefore improving the reliability.