Sharif Digital Repository

In order to achieve the international climate goals and to keep the global temperature increase below 2 °C, carbon capture and storage in large point sources of CO2 emissions has received considerable attention. In recent years, mitigation of CO2 emissions from the power sector has been studied extensively whereas other industrial point source emitters such as hydrogen industry have also great potential for CO2 abatement. This study aims to draw an updated comparison between different hydrogen and power cogeneration systems using natural gas and coal as feedstock. The goal is to show the relative advantage of cogeneration systems with respect to CO2 emission reduction costs. Accordingly, the... 

The growing worldwide demand for less polluting shapes of energy have led to a renewed interest in the use of Micro Combined Heat and Power (Micro CHP) technologies in the residential sector. Micro CHP have been introduced around Iran recently, and expected to diffuse more and more.In this paper, technical and economic studies for the use of Micro CHP in the different climate zones of Iran are executed. These zones are categorized in to five; Tehran, Rasht, Bandar Abbas, Ardebil and Yazd, based on weather conditions. Later on using an economic model, both annual energy savings and percentage of system profitability in each zone are calculated as well as reduction in annual emissions. It... 

Different reasons such as power system restructuring, electricity price variation in some hours of a day and growth in the fuel price, have led to more attention to demand response (DR) programmes for consumers. Two important issues in DR programmes are emergency demand response programming (EDRP) and Interruptible/Curtail able (I/C) programme that is utilised as interruptible load contracts (ILC). The EDDR is utilised to decrease the consumption in peak load or critical hours of the day. This occurs by means of customer's behaviour in response to the incentives. However, the curtailment of voluntarily loads in the critical hours considering the consumer requirements is an action that can be... 

Unit Commitment is the optimization process for minimizing the total cost of real power generation meeting the generating units and the system constraints. With the restructuring in power systems, the matter of great concern is the fuel cost and consequently electricity price increase in some hours of the day. Accordingly, the optimum performance of Demand Side Management (DSM) has been gaining great attention recently. In this paper, the effect of the optimum performance of Emergency Demand Response Program (EDRP) on the cost of the unit commitment problem considering the line flow constrains is scrutinized. Due to the fact that the simultaneous adoption of the unit commitment and demand... 

Growing interest in the intermittent renewable energy sources may jeopardize the flexibility of power systems. In order to improve the flexibility of modern power systems, the surplus electricity generated by renewable sources can be deployed into several carriers, such as natural gas and heating energy via power-to-gas (PtG) and power-to-heat (PtH) technologies. This paper proposes an optimal daily energy management model of residential energy hubs integrated with power-to-X technologies. The proposed energy hub is incorporated with PtG, PtH, combined heat and power (CHP) facilities, and thermal storage to meet the required electrical, gas, and heating demands. In order to capture the... 

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... 

New technologies such as smart homes and appliances and renewable energy production have been attracting much attention in recent years. In practice, the management of these technologies to get the minimum household payment has become a challenge due to the time-varying electricity price. In this paper, we propose a real time energy management system to manage the appliances and storages. The solar energy is charged in the storages and used together with the grid electricity to supply the appliances. The proposed management system uses an ILP-based Home Energy Management (ILPHEM) optimization engine. ILPHEM schedules appliances requests and storage usage based on updated real time input data... 

In future smart grids, energy storage systems (EESs) and demand response (DR) are expected to have an important role in balancing load changes arising from life-style of consumers and varying output of some renewable energy resources. However, activating DR and installing ESSs need huge investment forcing system owner to justify their effectiveness prior to any implementation. This paper presents a model to find the optimal capacity of EESs in distribution systems with demand responding to electricity price changes. The model aims at maximizing system owner profit by lessening total electricity provision costs. The model is formulated as a mixed integer non-linear programming problem. Due to... 

Cooperative cloud providers in the form of cloud federations can potentially reduce their energy costs by exploiting electricity price fluctuations across different locations. In this environment, on the one hand, the electricity price has a significant influence on the federations formed, and, thus, on the profit earned by the cloud providers, and on the other hand, the cloud cooperation has an inevitable impact on the performance of the smart grid. In this regard, the interaction between independent cloud providers and the smart grid is modeled as a two-stage Stackelberg game interleaved with a coalitional game in this article. In this game, in the first stage the smart grid, as a leader... 

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 disguise of traditional monopolistic electricity markets into deregulated competitive ones has made 'price forecasting' a crucial strategy for both producers and consumers: for the producers, to maximize their profit and hedge against price volatilities and for the consumers to manage their utility. Electricity price forecasting has thus emerged as a progressive field of study and numerous researches have been conducted to improve and optimize the price forecast methods. This paper proposes a precise and computationally efficient method to perform price forecasting in deregulated power markets. A locally linear neuro-fuzzy model is developed for price forecasting. The model is trained by... 

One of the efficient solar energy harvesting technics is the parabolic trough concentrated solar power plant. However, if the concentrated solar power plant were not equipped with a storage system, the power plant capacity factor would be deficient. Latent thermal energy storage system using phase change material (PCM) is a high energy density storage system to provide durable energy with a constant temperature. In this study, first, a dynamic analysis is performed implementing TRNSYS software on the parabolic trough concentrated solar power plant located in Shiraz, Iran. Consequently, this system is assisted by the latent thermal energy storage system to improve its performance and capacity... 

Real-time electricity prices along with demand-side potentials can provide distribution companies (DisCos) with considerable financial and technical benefits compared to the conventional flat prices. This paper incorporates demand response in DisCos' short-term decision model in a real-time pricing (RTP) environment wherein consumers are charged based on hourly varying prices. Besides the hourly RTP sale prices, the established model deals with other DisCo's short-term activities including hourly purchases from the grid, commitment of distributed generation (DG) units, dispatch of shunt compensators, and invocation of load curtailments (LCs). The stochastic nature of wholesale market prices... 

A massive focus has recently been made on demand response (DR) programs, aimed to the electricity price reduction, reliability improvement, and energy efficiency. Basically, DR programs are divided into twofold main categories, namely incentive-based programs and price- or time-based programs. The focus of this paper is on priced-based DR programs including consumer responses to the time differentiated pricing. Home load management (HLM) program is designed to control responsive appliances and charging/discharging cycles of plug-in hybrid electric vehicles (PHEVs) by the consumer. Uncertain parameters associated with PHEV, i.e. its departure/travelling time and energy consumption as well as... 

A massive focus has recently been made on demand response (DR) programs, aimed to the electricity price reduction, reliability improvement, and energy efficiency. Basically, DR programs are divided into twofold main categories, namely incentive-based programs and price- or time-based programs. The focus of this paper is on priced-based DR programs including consumer responses to the time differentiated pricing. Home load management (HLM) program is designed to control responsive appliances and charging/discharging cycles of plug-in hybrid electric vehicles (PHEVs) by the consumer. Uncertain parameters associated with PHEV, i.e. its departure/travelling time and energy consumption as well as... 

In this paper, hydrogen management in refineries is examined considering a new perspective to optimize refinery costs. In order to minimize the total annual cost in refineries a mixed-integer non-linear programming (MINLP) model has been developed. Retrofitting the hydrogen network and determining the hydrogen surplus capacity of refineries are the main outputs of the proposed model. Then, to utilize this surplus capacity and increase the profitability of refineries, surplus hydrogen is used to produce electricity and ammonia. The results of a case study showed that retrofitting of the hydrogen network can save 12% in the consumption of fresh hydrogen from hydrogen plants. After retrofitting... 

In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution... 

Increasing grid integration of intermittent renewable energy sources (RESs) and plug-in electric vehicles (PEVs) with uncertain behaviours have necessitated enhancing the flexibility requirements of distribution networks. Thus, in the state-of-The-Art distribution network expansion planning (DNEP) models, both flexibility requirements and high penetration of RESs and PEVs should be taken into consideration. In this respect, a novel collaborative planning model for power distribution network (PDN) and plug-in Electric Vehicle Parking Lots (EVPLs) is proposed in this paper, which leverages sizing, siting, and operation of EVPLs to enhance the distribution network flexibility. Also, to model... 

This paper finds near equilibrium prices for electricity markets with non-convexities due to binary variables, in order to reduce the market participants’ opportunity costs, such as generators’ unrecovered costs. The opportunity cost is defined as the difference between the profit when the instructions of the market operator are followed and when the market participants can freely make their own decisions based on the market prices. We use the minimum complementarity approximation to the minimum total opportunity cost model, from previous research, with tests on a much more realistic unit commitment model than in previous research, including features such as reserve requirements, ramping...