scholarly journals Multi-Objective Optimization of Steel Off-Gas in Cogeneration Using the ε-Constraint Method: A Combined Coke Oven and Converter Gas Case Study

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2741
Author(s):  
Sergio García García ◽  
Vicente Rodríguez Montequín ◽  
Marina Díaz Piloñeta ◽  
Susana Torno Lougedo
Keyword(s):  
Co2 Emissions ◽  
Electricity Market ◽  
Optimization Problems ◽  
Coke Oven ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Inflection Points ◽  
Decision Making Processes ◽  
Constraint Method

Increasingly demanding environmental regulations are forcing companies to reduce their impacts caused by their activity while defending the economic viability of their manufacturing processes, especially energy and carbon-intensive ones. Therefore, these challenges must be addressed by posing optimization problems that involve several objectives simultaneously, corresponding to different conditions, and often conflicting between. In this study, the residual gases of an integral steel factory were evaluated and modeled with the goal of developing an optimization problem considering two opposing objectives: CO2 emissions and profit. The problem was first approached in a mono-objective manner, optimizing profit through Mixed Integer Linear Programming (MILP), and then was extended to a bi-objective problem solved by means of the ε-constraint method, to find the Pareto front relating profit and CO2 emissions. The results show that multiobjective optimization is a very valuable resource for plant managers’ decision-making processes. The model makes it possible to identify inflection points from which the level of emissions would increase disproportionately. It gives priority to the consumption of less polluting fuels. The model also makes it possible to make the most of temporary buffers such as the gas holders, adapting to the hourly price of the electricity market. By applying this method, CO2 emissions decrease by more than 3%, and profit amounts up to 14.8% compared to a regular case under normal operating conditions. The sensitivity analysis of the CO2 price and CO2 constraints is also performed.

scholarly journals Location Routing Problem with Consideration of CO2 Emissions Cost: A Case Study

2020 ◽  
Vol 21 (2) ◽  
pp. 225-234
Author(s):  
Ananda Noor Sholichah ◽  
Y Yuniaristanto ◽  
I Wayan Suletra
Keyword(s):  
Co2 Emissions ◽  
Time Windows ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Study Results

Location and routing are the main critical problems investigated in a logistic. Location-Routing Problem (LRP) involves determining the location of facilities and vehicle routes to supply customer's demands. Determination of depots as distribution centers is one of the problems in LRP.  In LRP, carbon emissions need to be considered because these problems cause global warming and climate change. In this paper, a new mathematical model for LRP considering CO2 emissions minimization is proposed. This study developed a new  Mixed Integer Linear Programming (MILP)  model for LRP with time windows and considered the environmental impacts.  Finally, a case study was conducted in the province of Central Java, Indonesia. In this case study, there are three depot candidates. The study results indicated that using this method in existing conditions and constraints provides a more optimal solution than the company's actual route. A sensitivity analysis was also carried out in this case study.

scholarly journals A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3781
Author(s):  
Sergio García García ◽  
Vicente Rodríguez Montequín ◽  
Henar Morán Palacios ◽  
Adriano Mones Bayo
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Coke Oven ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Integer Linear Programming Model ◽  
Converter Gas

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.

scholarly journals Optimization of an Inter-Plant Hydrogen Network: A Simultaneous Approach to Solving Multi-Period Optimization Problems

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1548
Author(s):  
Rusong Han ◽  
Lixia Kang ◽  
Yinghua Jiang ◽  
Jing Wang ◽  
Yongzhong Liu
Keyword(s):  
Hydrogen Exchange ◽  
Optimization Problems ◽  
Operating Conditions ◽  
Utilization Efficiency ◽  
Simultaneous Optimization ◽  
Optimization Approach ◽  
Industrial Case Study ◽  
Scheduling Scheme ◽  
Hydrogen Network

Inter-plant hydrogen integration can reduce the consumption of hydrogen utility in petrochemical parks. However, the fluctuation of operating conditions will lead to complex multi-period problems of hydrogen network integration. This work develops a simultaneous optimization approach to solving multi-period optimization problems for the inter-plant hydrogen network. To do this, we consider the inter-plant hydrogen integration and the fluctuation of operating conditions in each plant at the same time, and aim to minimize the total annualized cost of the entire hydrogen system of all plants involved. An industrial case study of a three-plant hydrogen network with seven subperiods was adopted to verify the effectiveness of the proposed method. Results show that the optimal structure and the corresponding scheduling scheme can be obtained when the lowest cost of the system is targeted. Compared with the stepwise methods, the proposed approach features taking the characteristics of all subperiods into account simultaneously and making the structure of the hydrogen network much more effective and economical. For the scheduling schemes, the utilization efficiency of the internal hydrogen sources is increased by hydrogen exchange among the plants.

scholarly journals Industrial consumers’ electricity market participation options: a case study of an industrial cooling process in Denmark

2021 ◽  
Vol 4 (S2) ◽  
Author(s):  
Nicolas Fatras ◽  
Zheng Ma ◽  
Bo Nørregaard Jørgensen
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Market Price ◽  
Industrial Process ◽  
Operating Conditions ◽  
Comparative Approach ◽  
Market Participation ◽  
Cooling Process ◽  
Process Flexibility

AbstractIn a deregulated market context, industrial consumers often have multiple market participation options available to bid their flexible consumption in electricity markets and thereby reduce their electricity bill. Yet most participation strategies for demand response are developed in a fixed and predefined set of submarkets. Meanwhile, little literature has compared multiple market options for market participants. Therefore, this paper proposes a comparative approach between available market options to evaluate savings from different market participation options. More specifically, this study implements an optimisation program in Python to investigate the impacts of changes in an industrial process’ flexibility on savings with different market participation options. The optimisation program is tested with a case study of an industrial cooling process in three Danish submarkets (day-ahead, intraday, and regulating power markets). The market participation options are formed by different combinations of these three submarkets, and the type and amount of process flexibility are varied by changing time and load constraints in the optimisation program. The results show that bidding in market options with multiple submarkets yields higher savings than single-market bidding, but that increases in available flexibility impact savings in each market option differently. Increased flexibility will only bring additional savings if it allows to take further advantage of price variations in a market option. Additionally, increases in savings with flexibility depend on the considered type of flexibility. These changes in relative savings between market options at each flexibility level imply that the optimal market option is not a static choice for a process with variable operating conditions. The optimal market option for an industrial consumer depends not only on market price signals, but also on the type and amount of available flexibility.

scholarly journals Electricity Portfolio Optimization for Large Consumers: Iberian Electricity Market Case Study

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2249 ◽  
Author(s):  
Emanuel Canelas ◽  
Tânia Pinto-Varela ◽  
Bartosz Sawik
Keyword(s):  
Portfolio Optimization ◽  
Electricity Market ◽  
Value At Risk ◽  
Programming Model ◽  
Spot Market ◽  
Mixed Integer ◽  
Conditional Value At Risk ◽  
Expected Cost ◽  
Seasonal Behavior

Electricity markets are nowadays flooded with uncertainties that rise from renewable energy applications, technological development, and fossil fuel prices fluctuation, among others. These aspects result in a lumpy electricity prices for consumers, making it necessary to come up with risk management tools to help them hedge this associated risk. In this work a portfolio optimization applied to electricity sector, is proposed. A mixed integer programming model is presented to characterize the electricity portfolio of large consumers. The energy sources available for the portfolio characterization are the day-ahead spot market, forward contracts, and self-generation. The study novelty highlights the energy portfolio characterization for players denoted as large consumers, which has been overlooked by the scientific community and, focuses on the Iberian electricity market as a real case study. A multi-objective methodology is explored, using a weighted-sum approach. The expected cost and the conditional value-at-risk (CVaR) minimization are used as objective function. Three case studies illustrate the model applicability through the characterization of how the portfolio evolves with different demand profiles and how to take advantage from seasonality characteristic in the spot market. A scenario analysis is explored to reflect the uncertainty on the price of the spot market. The expected cost and CVaR are optimized for each case study and the portfolio analysis for each risk posture is characterized. The results illustrate the advantage to reduce costs and risk if the prices seasonality is considered, triggering to an adaptive seasonal behavior, which support the decision-maker decision towards its goals.

scholarly journals Approximating Nonlinear Relationships for Optimal Operation of Natural Gas Transport Networks

Processes ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 198 ◽  
Author(s):  
Kody Kazda ◽  
Xiang Li
Keyword(s):  
Natural Gas ◽  
Piecewise Linear ◽  
Approximation Error ◽  
Compressibility Factor ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Nonlinear Relationships ◽  
The Common

The compressor fuel cost minimization problem (FCMP) for natural gas pipelines is a relevant problem because of the substantial energy consumption of compressor stations transporting the large global demand for natural gas. The common method for modeling the FCMP is to assume key modeling parameters such as the friction factor, compressibility factor, isentropic exponent, and compressor efficiency to be constants, and their nonlinear relationships to the system operating conditions are ignored. Previous work has avoided the complexity associated with the nonlinear relationships inherent in the FCMP to avoid unreasonably long solution times for practical transportation systems. In this paper, a mixed-integer linear programming (MILP) based method is introduced to generate piecewise-linear functions that approximate the previously ignored nonlinear relationships. The MILP determines the optimal break-points and orientation of the linear segments so that approximation error is minimized. A novel FCMP model that includes the piecewise-linear approximations is applied in a case study on three simple gas networks. The case study shows that the novel FCMP model captures the nonlinear relationships with a high degree of accuracy and only marginally increases solution time compared to the common simplified FCMP model. The common simplified model is found to produce solutions with high error and infeasibility when applied on a rigorous simulation.

scholarly journals Robust operation of microgrid energy system under uncertainties and demand response program

2020 ◽  
Vol 17 (2) ◽  
pp. 1005
Author(s):  
Sahar Seyyedeh Barhagh ◽  
Amin Mohammadpour Shotorbani ◽  
Behnam Mohammadi-Ivatloo ◽  
Kazem Zare ◽  
Ali Farzamnia
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Optimization Problems ◽  
Energy Systems ◽  
Stochastic Scheduling ◽  
Energy System ◽  
Optimization Method ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Demand Response Program

<span>Microgrid energy systems are one of suitable solutions to the available problems in power systems such as energy losses, and resiliency issues. Local generation by these energy systems can reduce the role of the upstream network, which is a challenge in risky conditions. Also, uncertain behavior of electricity consumers and generating units can make the optimization problems sophisticated. So, uncertainty modeling seems to be necessary. In this paper, in order to model the uncertainty of generation of photovoltaic systems, a scenario-based model is used, while the robust optimization method is used to study the uncertainty of load. Moreover, the stochastic scheduling is performed to model the uncertain nature of renewable generation units. Time-of–use rates of demand response program (DRP) is also utilized to improve the system economic performance in different operating conditions. Studied problem is modeled using a mixed-integer linear programming (MILP). The general algebraic modeling system (GAMS) package is used to solve the proposed problem. A sample microgrid is studied and the results with DRP and without DRP are compared. It is shown that same robustness is achieved with a lower increase in the operation cost using DRP.</span>

scholarly journals Consumer savings, price, and emissions impacts of increasing demand response in the Midcontinent electricity market

2018 ◽  
Author(s):  
Steve Dahlke ◽  
Matt Prorok
Keyword(s):  
Co2 Emissions ◽  
Demand Response ◽  
Electricity Market ◽  
Supply And Demand ◽  
Operating Conditions ◽  
High Price ◽  
Demand Model ◽  
Emissions Reductions ◽  
Market Effects ◽  
Increasing Demand

This paper estimates consumer savings, CO2 emissions reductions, and price effects from increasing demand response (DR) dispatch in the Midcontinent Independent System Operator (MISO) electricity market. To quantify market effects, we develop a dynamic supply and demand model to explore a range of DR deployment scenarios. The study is motivated by the existence of regulatory and market rule barriers to market-based deployment of DR resources in the MISO region. We show annual consumer savings from increased market-based DR can vary from $1.3 million to $17.6 million under typical peak operating conditions, depending on the amount of DR resources available for market dispatch and the frequency of deployment. Consumer savings and other market effects increase exponentially during atypical periods with tight supply and high prices. Additionally, we find that DR deployment often reduces CO2 emissions, but the magnitude of emissions reductions varies depending on the emissions content of marginal generation at the time and location of deployment. The results of this study suggest regulators and other stakeholders should focus policy efforts to reducing regulatory barriers to DR deployment in wholesale markets, particularly in locations that experience high price spikes, to improve market efficiency and achieve cost savings for consumers.

scholarly journals Power Plant Cooperation In District Heating Considering Open Electricity Market

2021 ◽  
Vol 58 (3) ◽  
pp. 66-81
Author(s):  
R. Oleksijs ◽  
A. Sauhats ◽  
B. Olekshii
Keyword(s):  
Electricity Market ◽  
Mixed Integer Linear Programming ◽  
District Heating ◽  
Heat Energy ◽  
Mixed Integer ◽  
Energy Market ◽  
Market Participants ◽  
Hourly Data ◽  
Total Profit

Abstract The paper analyses the possibilities to form a coalition of several heat energy providers in order to participate in the district heating market considering the open electricity market. Cooperation would allow the participants to better dispatch the existing energy sources and would ensure higher total profit for the participants. The objective function for such a cooperation is provided. To optimise the operation of the coalition, mixed integer linear programming is used, considering constraints of different heating energy market participants and the need to fulfil heating energy balance. If any additional profit is made, it is shared between coalition participants according to the Shapley value, which grants interest for market participants to form the coalition. Case study based on historical hourly data is provided and numerical results are presented in the paper.

scholarly journals Transforming Romanian school buildings in prosumers. An opportunity for increasing the energy efficiency in electrical networks and reducing the environmental impact of the power distribution sector

2020 ◽  
Vol 180 ◽  
pp. 02009
Author(s):  
Mircea Scripcariu ◽  
Cristian Gheorghiu ◽  
Ioan-Sevastian Bitir-Istrate ◽  
Mihaela-Madalina Bonea
Keyword(s):  
Energy Efficiency ◽  
Electricity Market ◽  
Large Scale ◽  
Service Providers ◽  
Operating Conditions ◽  
Environmental Benefits ◽  
Communist Regime ◽  
School Buildings ◽  
Geographical Regions

In the last decades, electricity systems suffer crucial transformations from integrated networks with a unidirectional flow, to decentralized, bidirectional flow networks. The stakeholders of this large-scale business have changed or improved their role. Electricity distribution companies are becoming service providers and end-users are becoming electricity producers. With the legislation issued in 2018, a new stakeholder was born on the Romanian electricity market, the prosumer. So, the decentralization reached an extreme by giving the smallest end-user the opportunity to become an electricity producer. In the first paragraph of this paper, authors summarize provisions of most recent energy strategies issued by the Romanian Government and the regulatory framework for incentivizing this market player. Given the growing interest of local administration in energy efficiency and pollution reduction, authors consider that schools can play a major role in fulfilling ambitious environmental targets. Most school buildings date from the communist regime and have a rather similar design. In their energy management programmes, municipalities consider energy efficiency in school buildings and authors present the case study of a school in the city of Ploiesti, one of the largest in southern Romania. A brief description of the electricity end-use systems is presented. Before any measure is taken on the supply-side, school’s administration needs to implement the demand-side measures. Next, these measures are investigated, and the results of the technical-economic analysis are presented. In southern Romania, photovoltaic (PV) solutions have better operating conditions and for this case study the solution for local generation with PV panels is presented. In the paper, authors are making an in-depth investigation of extending the prosumers model, with local PV generation on school buildings, over most of Romanian geographical regions. The carbon footprint is calculated, and the environmental benefits of this integrated approach are highlighted.

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