فصلنامه پژوهش های سیاستگذاری و برنامه ریزی انرژی
سال ششم شماره 3 (پاییز 1399)

The limitations on resources of fossil fuels and their destructive effects on the environment have made renewable energy sources more attractive and between these sources, energy from biomass called bioenergy has a special place due to the wide range of resources and other benefits. The purpose of this research is to provide a bi-objective multi-period linear programming model to design the supply chain of bioenergy from various types of biomasses using anaerobic digestion and transesterification processes. Two types of biomass considered as feedstock are microalgae and Jatropha. The first objective function maximize the value of the total benefit and the second objective function minimize the amount of water consumption. Selection of raw material resources, locating the production facilities and raw material warehouses, value of optimal material flows, etc. are some of the decisions made by the model. The performance of the proposed model is evaluated and validated through conducting a real case study in Iran.

Excessive consumption of energy in Iran and, consequently, environmental pollution are serious challenges facing the country. Therefore, promoting energy efficiency in different sectors, especially in the industrial sector can be considered. Then the effective factors on energy efficiency should be considered carefully to make the necessary policies. Due to the importance of the industrial sector as the main driver of growth and value added, the best combination of factors affecting energy efficiency in the five energy-intensive industries for the firms of 10 employees and more during 1995-2015 was selected. The Gamma test results show that the best combination of variables affecting the energy efficiency of industries include environmental variables of technology, good governance, size of government, trade openness and real energy price as well as micro variables such as technical structure of production, capital price and energy consumption. According to the Data Envelopment Analysis, the average efficiency of all energy industries in the study period was about 68% and the food industry had a higher efficiency than the other industries.

Water requirements in many large water supply systems are provided by mixing water withdrawal from surface and underground resources with different quantity and quality.Water supply from underground sources requires energy consumption and surface water resources are limited and unstable.The aim of this research is managing optimal supply of required water of system with minimum energy cost and minimum water withdrawal from surface sources, meanwhile maintaining quantitative and qualitative stability of the system.This goal is achieved by optimizing operation schedule of pumps by managing energy consumption and optimizing changes in harvest discharge and mixing ratio of water sources.Differences between this study and similar studies, is the definition of multiple objectives, adding constraints like water quality in stability of the system, and assumption of harvest discharge and mixing ratio of water sources as variable.By considering continuity and energy rules and features of the system, system hydraulic is modeled mathematically and then by simulation in Vensim software with mathematical model assistance, model validation based on comparison with the actual data has evaluated.A multi-objective optimization is solved by using GAMS software.Finally, based on the goals of system administrators, sensitivity analysis on input data and results performed ,and optimal scenarios for managing the water supply system are presented.According to research findings,optimizing the water supply system can lead to 21% reduction in peak load consumption and 5% in energy costs .By considering just pumping stations, we save 37% in peak load consumption and 13% in energy costs.

Management and optimization of energy consumption has been importantly considered by policy-makers in the field of energy and environment from the perspective of energy security and environmental considerations. In this study, nondominated sorting genetic algorithm (NSGAII) was applied to determine the optimal share of fossil energy sources for energy intensive industries of Iran including The Manufacture of food products and beverages, The Manufacture of coke, refined petroleum products and nuclear fuel, The Manufacture of chemicals and chemical products, The Manufacture of other non-metallic mineral products and The Manufacture of basic metals. According to which the share of kerosene, 0.098%, 0.17%, 0.016%, 0.05%, 0.014%, the share of diesel, 12.88%, 0.93%, 0.62%, 1.97%, 0. 96%, the share of natural gas, 68.81%, 85.25%, 98.29%, 80.32%, 98%, the share of liquefied gas, 0.18%, 2.17%, 0.08%, 2.66%, 0.33%, the share of gasoline, 1.32%, 0.29%, 0.37%, 0.15%, 0.052% and the share of heavy fuel oil 16.7%, 11.18%, 0.62%, 14.83% , 0.65%, was obtained respectively. Then, the study utilized data envelopment analysis (Slack-Based measures) to measure the environmental and economic efficiency in some selected sub-sectors of industry by means of optimal amounts and then compared the results with the real amounts of energy consumption during 2011, 2014, 2015, and 2016. The results of optimization model compared with the real share of energy consumption that indicates the improvement of economic and environmental efficiency in the years under review.

One of the requirements for the development of societies and organizations is innovation, change in policies and policies, and the use of creative models in decision making. To achieve this goal, organizations must explore opportunities and identify new solutions and possibilities, and apply innovation in decisions. How to identify these opportunities and use them has always been a concern of policy makers and efforts have been made in this regard, but a comprehensive model in our country that can lead to entrepreneurial decision-making in a government organization has not been presented so far. Therefore, we sought to identify the dimensions, factors and elements affecting the policy entrepreneurship in the thermal power generation production policy making process and to present a suitable model for policy entrepreneurship for this field. To achieve this goal, a fundamental research based on a combined exploratory method was conducted. For this purpose, in the quality section, interviews were conducted with 18 experts in the field of electricity generation who were selected through the snowball sampling method. In the interview process, 244 open codes, 84 selective themes and 16 main themes were identified and the policy entrepreneurship model was presented in three dimensions: contextual, structural and behavioral. In the quantitative part, using a questionnaire and after assessing its content validity, based on the results of one-sample t-test, the effect of the components identified in the qualitative part on entrepreneurship was confirmed and the components were ranked based on the Friedman test.

The main purpose of this study is to design a mentoring model in Iran Grid Management Company. This research has been done with a qualitative approach. Participants in this study are 18 managers of Iran Grid Management Company who are active in the field of technology, engineering and human resources and participated in the research through purposeful sampling and theoretical saturation rule. Data were collected using semi-structured interviews. Validity of interview questions was done by content validity ratio (CVR) method and applying the opinions of 5 management experts and all participants in the study. The method of data analysis is inductive content analysis using coding at three levels: open, axial and selective. Findings indicate the identification of three categories of personal development, organizational development and communication development, each of which has several components. In the category of personal development, the components of knowledge, personality and job, in the category of organizational development, the components of management, motivation and human resources and in the category of communication development, the component of customers / stakeholders were identified.The results showed that management, personality and job are the most important components and three aspects of the mentoring pyramid in the company. Effective mentoring depends on the attitude of senior management and how to organize, direct and supervise matters and pay attention to the personality and job component.

Electricity has been considered as a pivotal product for sustainable development. As Iran has access to the high level of fossil fuel resources, the major proportion of Iranchr('39')s power generation belongs to thermal power plants. In this regard, the issue that all governments have faced is financing the initial capital costs of these projects, which plays a crucial role in providing a continuous electricity supply. In this paper, the most significant criteria and efficient methods of financing thermal power plants in Iran are discussed. A sample of 18 experts working in thermal power plants financing was used and the AHP model is employed to prioritise the efficient financing methods. Results indicate that financing through Islamic bonds (SUKUK) has the highest level of efficiency among funding methods and the applicability of funding source is the most important criterion in choosing the most efficient method of financing for these projects in Iran.