Production scheduling is the most important and influential issue in open pit and underground mining design and planning. The main purpose of mine production planning is time scheduling and determination of mine activities sequencing under some technical and extraction constraints in order to achieve one of the following goals: maximizing Net Present Value (NPV), the amount of ore extraction or mine life. Underground mine planning optimization which is used to determine the sequence of stopes extraction, is difficult due to the complexity of decision making and the interaction between existing constraints. Since, mathematical programming techniques are capable for solving complex and multi-limiting problems, they can be used for optimization purposes. In this study, after reviewing previous studies on the design and planning of underground mine production, the step by step explanation of a proposed model based on Integer Programming (IP) has been addressed. In order to validate proposed model, an example of 9 stopes was considered. First, the sequence of extraction was carried out using manual design and then using extended mathematical model in GAMS/CPLEX software. The current NPV obtained by manual production scheduling was 8.211 million dollars. While, this value for mathematical model was 8.331 million dollars. In other words, NPV value in mathematical model was 1.46% higher than manual method which indicate the power of mathematical programming for solving complex problems.

In this study, the feasibility of achieving the net-zero energy (NZE) target has been studied in a bioethanol production complex (Zist Faravarde Sepahan) based on different NZE definitions, including net-zero site energy, net-zero source energy, net-zero energy cost, net-zero energy emission, and net-zero exergy. In the technical investigations, the energy required for each approach has been determined, and then the corresponding photovoltaic power plant has been simulated in photovoltaic systems software (PVsyst) and transient systems simulation program (TRNSYS) by considering the generated and consumed energy. Afterward, the annual cumulative data of generation, consumption, export, and delivery energies of the complex have been extracted in the transient hourly conditions. The load matching, self-consumption, and electricity self-sufficiency indices were determined and compared in different approaches based on the hourly data. In the next step, β factor that is a fraction of the net present value (NPV) definition has been studied for the economic evaluation of the approaches in three pricing strategies: a) Buy all sell all (BASA), b) Net energy measurement (NEM) and c) Net billing (NB). Based on the technical evaluation, the net-zero energy cost approach is the most appropriate option to achieve the NZE target in the complex. Considering economic considerations, the net-zero energy cost in the BASA pricing strategy with a nominal power of 1.2 MWp < /sub> and a self-consumption index of 84.2% has the best results in both technical and economic investigations. β factor and NPV indices are 1.97 and $ 1,579,512 in this approach, respectively. The profitability phase (NPV = 0) will start after 10.1 years operation of the system.

In the present study, two proposed designs for compressed air storage systems, one equipped with heat recovery and the other without it, are presented and their technical analysis is performed. The costs of each project are evaluated and economic analysis including Net Present Value (NPV), Internal Rate of Return (IRR), Profitability Index (PI), and Discounted Payback Period (DPBP) is performed. These analyses are presented for storage energy values of 80, 220, 360, 480, 640, and 1000 kWh and storage pressures of 50, 100, 150, 200, 250, 300, 350, 400, and 450 bar. The results of the technical and economic analysis show that these systems are more justifiable to produce higher capacities at lower storage pressures. Finally, using the results of this analysis, the optimal energy storage plan of 640 kWh with storage pressure of 50 bar is proposed. The results of this study can be used to select a suitable compressed air storage system for peak shaving during peak hours of power consumption.

Determining the transition limit from the open pit mining to an underground mining method is one of the key decisions where there is the possibility to mine using both open pit and underground mining methods. Transition level is a depth where open pit mining is the best choice above this depth and underground mining is prioritized below it regarding the technical and economic aspects. In the early-stage mine planning studies, including the determination of transition limit, simplicity, practicality, and quickness of decision making are of the requirements, while achieving the acceptable answers is regarded. In this research, a practical approach based on combining Lerchs and Grossman algorithm and the Equilibrium Stripping Ratio (ESR) method is proposed to determine the transition limit. For this purpose, firstly nested and developing pits are generated with the objective of maximizing the net present value (NPV), then the Incremental Stripping Ratios (ISR) of each of these optimal developing pits are calculated. According to the alternative underground mining method(s), the ESR is calculated and finally, the transition limit will be determined comparing the ISR of these developing pits and the calculated ESR. In the present research, this approach is applied to determine the transition level in an iron ore deposit. To verify the determined transition limit, calculating the cumulative net present value shows that mining by underground method below the determined transition level can increase the NPV by 23% compared to continuing open pit mining.