Optimal Allocation Of Energy Resources Research Articles

Research on the Optimal Allocation of Energy Resources to Minimize Costs Associated with Greenhouse Gas Emissions

Research on the Optimal Allocation of Energy Resources to Minimize Costs Associated with Greenhouse Gas Emissions

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. This study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

Decentralized cooperative scheduling of prosumer flexibility under forecast uncertainties

Scheduling of prosumer flexibility is challenging in finding an optimal allocation of energy resources for heterogeneous prosumer goals under various forecast uncertainties and operation constraints. This study addresses this challenge by introducing a bottom-up framework for cooperative flexibility scheduling that relies on a decentralized network of scheduling agents to perform a coordinated decision-making and select a subset of households’ net load schedules that fulfills the techno-socio-economic prosumer objectives in the resource operation modes and ensures the reliability of the grid. The resource flexibility in terms of alternative operation schedules is mathematically modeled with multiobjective optimization that attains economic, environmental, and energy self-sufficiency prosumer goals with respect to their relative importance. The coordination is achieved with a privacy-preserving collective learning algorithm that aims to reduce the aggregated peak demand of the households considering prosumers’ willingness to cooperate and accept a less preferred resource schedule. By utilizing the framework and real-world data, the novel case study is demonstrated for prosumers equipped with solar battery systems in a community microgrid. The findings show that the flexibility scheduling with an optimal prosumer cooperation level decreases the global costs of collective peak shaving by 83% while increasing the local prosumer costs by 28% in comparison with noncooperative scheduling. However, the forecast uncertainty in net load and parameters of the frequency containment reserve causes imbalances in the planned schedules. It is suggested that the imbalances can be decreased if the flexibility modeling takes into account variable specific levels of forecast uncertainty.

Impact of Social Welfare Metrics on Energy Allocation in Multi-Objective Optimization

Resource allocation problems are at the core of the smart grid where energy supply and demand must match. Multi-objective optimization can be applied in such cases to find the optimal allocation of energy resources among consumers considering energy domain factors such as variable and intermittent production, market prices, or demand response events. In this regard, this paper considers consumer energy demand and system-wide energy constraints to be individual objectives and optimization variables to be the allocation of energy over time to each of the consumers. This paper considers a case in which multi-objective optimization is used to generate Pareto sets of solutions containing possible allocations for multiple energy intensive consumers constituted by commercial greenhouse growers. We consider the problem of selecting a final solution from these Pareto sets, one of maximizing the social welfare between objectives. Social welfare is a set of metrics often applied to multi-agent systems to evaluate the overall system performance. We introduce and apply social welfare ordering using different social welfare metrics to select solutions from these sets to investigate the impact of the type of social welfare metric on the optimization outcome. The results of our experiments indicate how different social welfare metrics affect the optimization outcome and how that translates to general resource allocation strategies.

An optimal energy resource allocation framework for cellular networks with power grid interruptions

In this paper, we investigate the problem of optimal allocation of renewable energy resources to power base stations (BSs) in cellular networks while accounting for possible power failures in the utility grid. The allocation problem under investigation is formulated as a mixed integer non-linear programming, which is then decomposed, due to its complexity, and solved as two interdependent problems with the help of deterministic and metaheuristic techniques. We propose an allocation algorithm that jointly aims at optimizing the allocation of individualized green energy resources to simultaneously power the BSs with the grid as well as minimizing the overall system costs. Cost minimization is achieved by selecting the optimal types and sizes of the used photovoltaic (PV) panels and batteries in addition to optimally scheduling the charging and discharging of the selected batteries. This is done while limiting PV curtailment and any expected loss of cellular services at the times of power outage. Finally, the effectiveness of the proposed algorithm is demonstrated through the simulation of a sample case of a typical BS where Markov Chain Monte Carlo simulations are carried out to account for the uncertainty of the output of the PV panels and the grid failures.

Optimal Energy and Reserve Market Management in Renewable Microgrid-PEVs Parking Lot Systems: V2G, Demand Response and Sustainability Costs

Vehicle-to-grid (V2G) technology heralds great promise as a demand-side resource to contribute to more efficient grid management and promote the use of decentralized renewable energy. In this light, we propose a new optimization model for the sustainable energy and reserve market management in renewable-driven microgrid (RMG) plug-in electric vehicles (PEVs) parking lot systems. The RMG is composed of a hybrid photovoltaic/wind/hydrogen energy and storage system, along with local dispatchable generation units and bidirectional grid connection. The RMG is coupled to a smart PEVs parking lot, which is equipped with grid-to-vehicle (G2V) and V2G technologies allowing for not only PEVs aggregation and control but also optimal allocation of energy resources. Time-of-use (TOU) prices are considered in a demand response program (DRP) to enhance both economic and environmental performances by encouraging end-users to shift their energy demands from peak to off-peak time periods. Additionally, the model accounts for an economic incentive to PEVs owners to compensate for battery degradation. The integrated system eco-efficiency is evaluated through the application of the novel life cycle assessment-based Eco-cost indicator. The resulting mixed-integer linear programming model to minimize sustainability costs is implemented in GAMS and solved to global optimality. Different case studies are performed to demonstrate the effectiveness of the proposed modelling approach. Energy analyses results reveal that the optimal G2V-V2G operation, allied to TOU prices in a DRP, and reserve market management can reduce around 42% the energy and environmental costs of the RMG-PEVs parking lot system.

Study on the Comprehensive Benefit Evaluation of Transnational Power Networking Projects Based on Multi-Project Stakeholder Perspectives

Interconnection of transnational power grids plays an important role in realizing the optimal allocation of energy resources. It can also deepen regional economic cooperation, achieve energy conservation and emission reduction, and improve people’s livelihood. This paper constructs a comprehensive benefit evaluation index system for transnational power networking projects which is suitable for the four stakeholders of investors, international lending institutions, sending-oriented states, and receiving-oriented states. Therefore, on the basis of this index system, this paper adopted the weight determination method based on the order relation method and Gini coefficient method to synthesize subjective and objective information. Then the comprehensive benefit evaluation of such projects was carried out by matter-element extension model with grey relational projection value. Therefore, the problem with the Euclid approach degree leading to a low discrimination of many samples to be evaluated was effectively solved. The final empirical analysis results showed that the focus and evaluation results of the comprehensive benefits of such projects from the perspective of different stakeholders were quite different. The results of comprehensive benefit evaluation will improve the accuracy of decision-making and the objectivity of evaluation, so as to provide decision-making references for different stakeholders.

Welding technology of ultra high voltage transmission steel pipe tower butt welded joint by MIG welding

In twenty-first Century, China vigorously promoted the research and construction of AC and DC transmission technology in order to ensure the optimal allocation of energy resources in a large scale[1]. The transmission line is the core of the power grid, which plays the role of transmission, transformation and distribution of electric energy, and each tower is the core component of the transmission line. At present, because the force of the steel tube tower is more reasonable, it has been widely used in the construction of UHV, and the link of the key position of the steel tube tower is welded, so the quality of the welding is of great significance to the construction of the whole network frame. For the welding of the steel tube tower, the manual semi automatic CO2 gas shielded welding is mostly used. Because of the characteristics of the protective gas medium, it is easy to produce a large number of splashes and not easy to clean up during the welding process. It is easy to make the weld penetration rate and forming decline. It is effective to use the melting pole mixture gas protection welding, If we can make a scientific welding standard, it is possible to reduce the occurrence of welding spatter, achieve the purpose of improving welding efficiency and controlling manufacturing cost.

Application of welding simulation training system

The situation of the reverse distribution of energy resources and load center in China determines that UHV transmission technology has a wide application space in China.[1]With the increasing size of UHV transmission line construction, the application of welding technology for UHV steel tube tower is becoming more and more important, and the training of welding technology is accompanied by the use of a large number of consumables. China vigorously promoted the research and construction of AC and DC transmission technology in order to ensure the optimal allocation of energy resources in a large scale[2].In order to further save the cost, this paper combines the increasingly mature virtual reality 3D technology, and applies the simulation training system to the system. In the training of MIG (MAG) welding skill of power grid steel structure, the characteristics and training flow of welding simulation training are introduced, and the application effect of the simulation training system is summarized. By constantly exploring new welding training mode, improving the shortcomings of traditional welding training and improving the overall training effect of welding workers.

Research on the Development Trend of Power Grid Interconnection In the Belt and Road

The interconnection of power grid infrastructure is a priority area for the construction of the B&R, which plays an important role in achieving optimal allocation of energy resources and deepening regional economic cooperation. Based on an analysis of the status, future development trend and challenges of power grid interconnection in the B&R area, the basic principles and overall strategy for promoting transnational power grid interconnection in the B&R is proposed.

A Fast Method for Reliability Evaluation of Ultra High Voltage AC/DC System Based on Hybrid Simulation

The construction and operation of the ultrahigh voltage power grid has solved the problem of optimal allocation of energy resources and played a key role in promoting social development. However, concerns about its safety have kept growing in recent years. In order to analyze the reliability of ultrahigh voltage AC/DC system combined with the quasi-Monte Carlo method and PSD-BPA simulation, the reliability model of various components and system is established, and the simulation speed is improved with accuracy ensured. In order to ensure the compatibility and efficiency of the software, we design the BPA-Matpower data interface, and the data translation from BPA to Matpower is realized by fourth conversion. Then, we propose an index system for reliability evaluation, concise and easy to compute, to reflect the reliability of the UHV grids and the characteristics of AC and DC systems. Based on actual regional powergrid, we compare the model in this paper with the traditional sequential Monte Carlo method, and carry out the analysis of the component sensitivity to study the multi-fault characteristics and the weakness of the system, and verify the scientific and effective result of this paper.

FCAW vertical welding of “V” butt plate in AC UHV transmission line construction

In twenty-first Century, China vigorously promoted the research and construction of AC and DC transmission technology in order to ensure the optimal allocation of energy resources in a large scale[1]. In the construction of AC UHV transmission line, the welding quality of tower and stiffening plate as the load bearing tower and the tension of the welded structure plays an important role in the overall quality of the steel structure. In the past, the welding process of semi automatic carbon dioxide solid core welding wire often has the characteristics of weld spatter not easy to clean up and low efficiency of welding. The semi-automatic CO2 flux cored arc welding, has the characteristics of current and voltage to adapt to a wide range, melting speed, has important significance for improving the process, this paper describes the technology in practical engineering applications, and developed the basic strategy of training for grid steel structure welding technicians. This paper also lists both V groove plate butt FCAW welding typical welding project, hope this welding process will continue to spread.

Energy resource allocation in Iran regarding targeted subsidies reform

ABSTRACTIran has enormous energy resources and owns the second largest oil and gas reservoirs in the world. Cheap domestic energy prices and energy subsidies had led to a rapid increase in domestic energy consumption in the country. In 2010, increasing domestic energy prices and targeted subsidies reform were implemented. The objective of this article is to allocate optimally to each end-user a certain amount of energy to be supplied by a given resource in Iran regarding targeted subsidies reform. For this purpose, energy demands of end-users are forecasted and the outcomes are used in a fuzzy linear programing model, which determines the best allocation of energy resources of Iran from 2012 to 2020. The results would provide a scientific basis for the optimal allocation of energy resources in meeting the future energy demand in Iran.

HEMS: a home energy market simulator

Stability issues in the electric power grid originate from the rising of renewable energy generation and the increasing number of electric vehicles. The uncertainty and the distributed nature of generation and consumption demand for optimal allocation of energy resources, which, in the absence of sufficient control reserve for power generation, can be achieved using demand-response. A price signal can be exploited to reflect the availability of energy. In this paper, market-based energy allocation solutions for small energy grids are discussed and implemented in a simulator, which is released for open use. Artificial neural network controllers for energy prosumers can be designed to minimize individual and overall running costs. This enables a better use of local energy production from renewable sources, while considering residents' necessities to minimize discomfort.

Optimal Energy Consumption Model in Transport

Transport is one of the most important components of infrastructure so far as the growth process of an economy is concerned. On the other hand a convergence of growing demand, resource constraints, and environmental imperatives will reshape our energy system. The future of production and consumption of the energy carriers and their correct and appropriate application in different sectors are of paramount importance. With a view to this and using a linear programming model, optimal allocation of energy resources to different sectors is discussed here. Meanwhile, political, economic, and environmental objectives are taken into consideration. To do so, the data related to 40 recent years are used for predicting energy demand in different consumption sectors and studying validity of model. In addition, allocation of oil and gas resources to different consumption sectors during 2013-2024 is discussed with respect to implementation of the targeted subsidies plan in Iran. The results of the present research provide programmers and decision-makers with appropriate approaches to offer a suitable programming on optimal allocation of energy resources.

A fuzzy linear programming model for allocation of oil and gas resources in iran with the aim of reducing the greenhouse gases

Energy plays a key role in sustainable development. Formulation of an energy model will help in the proper allocation of available energy resources. The objective of this article is to allocate optimally to each end user a certain amount of energy to be supplied by a given resource in Iran to reduce greenhouse gases. For this purpose, energy demands of end users are forecasted, and the outcomes are used in a fuzzy linear programming model, which determines the best allocation of energy resources in Iran from 2012 to 2020. The result shows a large portion of crude oil and natural gas will be allocated for exports. Transportation sector will be the major consumer of the petroleum products. Higher amounts of natural gas compared with the petroleum products will be allocated to power plants. Moreover, a considerable portion of natural gas should be injected into the oil reservoirs. These analyses would provide scientific basis for the optimal allocation of energy resources in meeting the future energy demand in Iran. © 2012 American Institute of Chemical Engineers Environ Prog, 32: 854–859, 2013

Kuwait Energy Profile for Electrical Power Generation

ABSTRACT The State of Kuwait, a major oil exporter, consumes a huge amount of its natural hydrocarbon resources to meet the rising demand for electricity. The forecasting of domestic energy demand and optimal allocation of energy resources are necessary requirements for a balanced energy policy. This article assesses the energy resources profile of Kuwait in order to reveal the potential base and level of utilization of resources. The analysis of the energy profile indicates that, in 2009, Kuwait had proven crude oil reserves of 104 billion barrels and 63 trillion cubic feet of natural gas reserves. Heavily sustained, subsidized electricity and water prices are the main factors behind the rise in irrational consumption (demand). The analysis revealed that the installed capacity of electricity and water supply can barely meet the rising demand. The article proposes sustainable strategies regarding the energy resources required for generating electricity. The strategic thrusts for the energy policy should n...

Energy Resource Allocation in Iran: A Fuzzy Multi-Objective Analysis

Energy plays a key role in the development of nations and provides vital services and means that improve quality of life. Formulation of an energy model will help in the proper allocation of available energy resources. The objective of this paper is to allocate optimally to each end-use a certain amount of energy to be supplied by a given resource in Iran. In this research, the energy allocation process is looked at from three points of view: policy, economy and environment. In this way, energy demands of end-uses are forecasted using neural networks and fuzzy linear regression methods. The outcomes are used in a fuzzy multi-objective linear programming model, which determines the optimum allocation of energy resources of Iran from 2011 to 2020. The results provide scientific basis for the optimal allocation of energy resources in meeting the future energy demand in Iran.

Technological impact on energy consumption in rainfed soybean cultivation in Madhya Pradesh

Madhya Pradesh is a state located in the central part of India, and grows 73% of soybean produced in India. In five villages located in various agro climatic regions of the state, 275 farmers cultivated soybean during 1997–1999, of which 239 farms had practiced rainfed cultivation. A total of 188 rainfed farms had used a combination of bullock and tractor power (mixed farming), constituting 67.6% of the farms surveyed. The energy consumption patterns of these farms were studied and a linear programming technique applied to determine optimal energy resource allocation for maximum yield obtainable under business-as-usual and improved cultivation practices. The results indicated that 40.2% additional yield over average yield (achieved by the farmers under study) of 1089 kg/ha can be obtained without major change in energy use pattern under business-as-usual cultivation practice. With the use of improved cultivation practices, a yield of 2274 kg/ha can be obtained through investment of 8118 MJ/ha. Adoption of the improved cultivation practice would improve energy productivity to 0.30 kg/MJ as compared to 0.179 kg/MJ presently achieved by the farmers.

A multiobjective programming approach to energy resource allocation problems

The optimal allocation of energy resources to various energy end uses is an important strategy for bridging the energy supply and demand gap in India. It has been recognized that the allocation should be guided by multiple criteria. A multiobjective programming model for such an allocation process is presented in the paper. The normative model has been applied for the households sector of Madras city. The model is solved using non pre-emptive goal programming. Variations in the original model have been made to build alternative scenarios. The results of the original model and the alternative scenarios indicate that the use of solar thermal energy, natural gas, LPG, fuelwood, kerosene and lignite should be promoted for cooking, and the use of grid electricity and diesel, should be promoted for meeting water pumping demands. They favour the use of electricity generated from diesel for lighting, and the use of solar photovoltaics for meeting the electricity demands of household appliances. The results also indicate that grid electricity and electricity generated from fuelwood should be promoted to meet the demands of all the four household end uses, and point to the need for more research into solar photovoltaics, which may become competitive for meeting household demands in the future.