Sharif Digital Repository

Despite the abundant renewable energy sources, the Iranian energy sector relies almost entirely on fossil fuel energy resources. Power sector is dominant source of CO2 emissions and responsible for about 35% of total CO2 emissions in the country. Additionally, long-term electricity demand of Iran is expected to grow quickly, which in turn requires extensive investment to meet the growing demand over the next decades. On the other hand, increasing domestic fossil fuel consumption had been a serious challenge due to high costs of oil and gas. Current study pays particular attention to the possible penetration rates of renewable electricity technologies and their implications for fossil fuel... 

Reinforcing the correlation between Gas and Electricity Systems (G&ESs) susceptible to diverse factors ranging from anthropogenic climate change to the advent of new conversion/generation technologies has remarkably brought into focus the co-expansion of G&ESs using a new concept so-called Energy Hub (EH) as well as the potential of storage systems. To assess the effectiveness of EH approach and the role of storages in the coordinated plans of G&ES, this study proposes a comprehensive EH-based planning model for co-expansion of G&ES supply chains with respect to the role of Gas Storage Systems (GSSs). As a Mixed-Integer Linear Programming (MILP) problem, the model is applied to a real... 

To attain an ongoing electricity economy, developing novel widespread electricity supply systems based on diverse energy resources are critically important. Several photovoltaic (PV) technologies exist, which cause various pathways to produce electricity from solar energy. This paper evaluates the competition between three influential solar technologies based on photovoltaic technique to find the optimal pathways for satisfying the electricity demand: (1) multicrystalline silicon; (2) copper, indium, gallium, and selenium (CIGS); and (3) multijunction. Besides the technical factors, there are other effective parameters such as cost, operability, feasibility, and capacity that should be... 

In a deregulated electric power system in which a competitive electricity market can influence system reliability, system analysts are rapidly recognizing that they cannot ignore market risks. This paper first proposes an analytical probabilistic model for the reliable evaluation of competitive electricity markets and then develops a methodology for incorporating the market reliability problem into composite power system reliability studies. The market reliability is evaluated using the Markov state space diagram. Since the market is a continuously operated system, the concept of absorbing states is applied to it in order to evaluate reliability. The market states are identified using market... 

Microgrids have emerged as a practical solution to improve the power system resilience against unpredicted failures and power outages. Microgrids offer substantial benefits for customers through the local supply of domestic demands as well as reducing curtailment during possible disruptions. Furthermore, the interdependency of natural gas and power networks is a key factor in energy systems’ resilience during critical hours. This paper suggests a probabilistic optimization of networked multi-carrier microgrids (NMCMG), addressing the uncertainties associated with thermal and electrical demands, renewable power generation, and the electricity market. The approach aims to minimize the NMCMG... 

Power systems are stretched across thousands of miles of diverse territories, often in remote locations, to generate and transfer the energy to geographically dispersed customers. The system is therefore subjected to a wide range of natural hazards which could potentially damage critical system components and cause interruption of electricity supply in some areas. To improve system resilience against natural hazards, management frameworks are required to identify hazardous areas and prioritize reinforcement activities in order to take the most out of the limited resources.Landslide is a natural disaster that involves the breakup and downhill flow of rock, mud, water, and anything caught in... 

As part of its Paris Agreement commitment, Iran pledged to decrease 4 % of its carbon dioxide (CO2) emissions from 2020 to 2030. About 29% of total emission in Iran belongs to electricity supply while energy consumption in other sectors (transport, household, and industry) have a lower share in CO2 emission. The main concern here is finding the optimal mix of power plants in the electricity supply system that should be deployed to meet Iran’s mentioned respective targets and considering simultaneously interests of consumers and producers in this energy system. So, we developed a non-linear mathematical programming model for Iran’s electricity system to address this concern with changing... 

In this paper, special focus is paid to the long-term adoption of renewable electricity technologies and their implications for emissions reductions in Iran. MESSAGE, as a bottom-up energy supply optimization model, is used to assess the lowest-cost technology options. The potential impacts of transitioning to a renewable electricity supply are quantified, and the investment requirement to achieve a low-carbon generation mix is estimated. Alternative scenarios are defined to evaluate the impact of fossil fuel prices, the carbon tax and government incentives on the utilization of renewable resources, national renewable targets, and emissions reductions. The prioritization of non-hydro... 

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new technologies, new energy trading strategies and a new deregulated environment. In the new deregulated energy market and considering the incentives coming from the technical and economic fields, it is reasonable to consider Distributed Generation (DG) as a viable option for systems reinforcement in competition with voltage regulator devices, to solve the lacking electric power supply problem and meet the load growth requirements with a reasonable price as well as the system power quality problems. The problem of optimal placement and size is formulated in two stages; minimization of... 

Expanding the electricity market into the retail domain calls for inexpensive mass-produced smart devices that enable the small customers to participate in local energy transactions by managing the energy production/consumption and submitting buy/sell bids to the market. In this context, this paper presents a mathematically proven as well as practical approach for bidding of an autonomous smart transactive agent in local energy markets. To reach this goal, behaviors of both riskneutral and risk-averse agents selling energy to the market are modeled taking into account expected profit and risk criteria. Based on this modeling procedure, an optimal multi-step quantity-price bidding strategy is... 

Machine learning (ML) is generating new opportunities for innovative research in energy economics and finance. We critically review the burgeoning literature dedicated to Energy Economics/Finance applications of ML. Our review identifies applications in areas such as predicting energy prices (e.g. crude oil, natural gas, and power), demand forecasting, risk management, trading strategies, data processing, and analyzing macro/energy trends. We critically review the content (methods and findings) of more than 130 articles published between 2005 and 2018. Our analysis suggests that Support Vector Machine (SVM), Artificial Neural Network (ANN), and Genetic Algorithms (GAs) are among the most... 

The Iranian government has set a target of a 20% share of non-fossil fuel electricity generation by 2030, whose main result is reducing Green House Gas (GHG) emissions (about 182 million tonnes in 2017) to achieve the targets pledged under the Paris Climate Accord. So, this paper presents a comprehensive model on the expansion of non-fossil technology to evaluate the impact of increasing their share in Iran’s electricity supply system. This analytical approach is based on system dynamics (SD) that was developed based on dynamic behavior of electricity market, with an emphasis on the expansion of non-fossil fuels (solar photovoltaics, wind turbines, expansion turbines, and hydro power) in the... 

Energy Return on Investment (EROI) is an indicator of how efficient is an energy supply system. In the present study, the conventional approach of EROI assessment is extended to include the equivalent energy investment needed for offsetting the life cycle environmental impacts. Moreover, the issue of allocation of the invested energy among different by-products is addressed. The EROI of multiple products has been specified using different benchmarks of price, energy content, exergy content, and exergy costs. The application of the concept is demonstrated through a case study of an Iranian oil production unit. The overall conventional and environmentally-extended EROI values of the produced... 

Nowadays, the increasing integration of variable renewable energies (VREs) in power systems have resulted in operational transformations of energy systems. Respectively, the high-amount of integrated VREs could cause severe-ramping in the net-load of energy systems due to abrupt changes in their power production. Accordingly, based on the limited flexibility capacity in transmission systems, severe ramping-up/down (RU/RD) in distribution systems should be addressed by employing local flexible resources (LFRs). Nevertheless, evolution of multi-agent structured distribution systems has limited the direct access of distribution system operators (DSOs) in scheduling of LFRs. Consequently, this... 

An algorithm for determining optimal reserve capacity in a power market is presented in this paper. Optimization process in the proposed algorithm is based on the cost-benefit trade off. Market clearance is executed with consideration of uncertainties of power system components in an aggregated environment. It is assumed that both generating units and interruptible loads participate in the reserve market. In addition, customers' reliability requirements are considered as constraints for decision making process of ISO. The rendered method considers random outages of generating units and transmission lines and determined outage of interruptible loads and employs Monte Carlo Simulation (MCS)... 

Implementation of various incentive-based demand response strategies has great potential to decrease peak load growth and customer electricity bill cost. Using advanced metering and automatic demand management makes it possible to optimize energy consumption, to reduce grid loss, and to release generation capacities for the sake of providing sustainable electricity supply. Executing an incentive-based program is a simple way for customers to monitor and manage their energy consumption, and therefore, to reduce their electricity bill. With these objectives, this paper examines the previously suggested load scheduling programs and proposes a new practical one for residential energy management.... 

The development of technologies such as micro turbines and gas furnaces has been the major driving force towards integration of electricity and natural gas networks in the EH (energy hubs). Besides, the existing power grids are getting smarter by implementing the new generation of information technologies and communication systems. In smart grid, the electricity suppliers can modify the customers' electrical load consumption by employing appropriate scheduling schemes such as DR (demand response) programs. In this paper, we consider the S. E. Hubs (smart energy hubs) framework, in which the customers can use EMS (energy management system) to access to the electricity and natural gas prices... 

An algorithm for determining optimal reserve capacity in a power market is presented in this paper. Optimization process in the proposed algorithm is based on the cost-benefit trade off. Market clearance is executed with consideration of uncertainties of power system components in an aggregated environment. It is assumed that both generating units and interruptible loads participate in the reserve market. In addition, customers' reliability requirements are considered as constraints for decision making process of ISO. The rendered method considers random outages of generating units and transmission lines and determined outage of interruptible loads and employs Monte Carlo Simulation (MCS)... 

The use of hybrid renewable energy has increased in recent years due to the growing environmental concerns caused by the consumption of fossil fuels. The purpose of this study was the economic-environmental feasibility of using hybrid energy systems in one of the most polluted and populated provinces in Iran, Isfahan province. Various components of the hybrid energy system such as wind turbine (WT), photovoltaic panel (PV), diesel generator (DG), converter (CV) along with two scenarios of energy storage including battery (BT) and hydrogen storage have been considered in modeling the energy system. Six scenarios were considered based on the combination of different components for supplying...