Effect of Increasing Number of Residential SOFC Cogeneration Systems Involved in Power Interchange Operation in Housing Complex on Energy Saving

2011 ◽  
Vol 8 (4) ◽  
Author(s):  
Tetsuya Wakui ◽  
Ryohei Yokoyama
Keyword(s):  
Energy Saving ◽  
Electric Power ◽  
Power Flow ◽  
Electric Power System ◽  
Mixed Integer ◽  
Load Factor ◽  
Power Demand ◽  
Cogeneration System ◽  
Housing Complex ◽  
Saving Effect

Residential solid oxide fuel cell cogeneration systems (R-FCGSs) have high generating efficiencies; however, they must be operated continuously because of their long warm-up times. Moreover, a reverse power flow from a residential cogeneration system to a commercial electric power system is not permitted in Japan. Because of these restrictions, it is considered that the R-FCGSs may not fully achieve their potential energy-saving effects in Japan. In order to improve the energy-saving effect of the R-FCGSs, the authors have been focusing on a power interchange operation using multiple R-FCGSs (IC) installed at residences in a housing complex as an application of a microgrid. In this operation, the electric power generated by the R-FCGSs is shared among the residences in the housing complex with no reverse power flow so that the electric load factor of the R-FCGSs may increase. This paper discusses the effect of increasing the number of the R-FCGSs involved in the IC on energy saving by conducting optimal operational planning based on mixed-integer linear programming. The numerical analyses for various numbers of target R-FCGSs, with a maximum of 20, clarify that the energy-saving effect of introducing the IC is not correlated with increasing the number of target R-FCGSs, but generally dominated by the total heat to power demand ratio and hourly variations in the electric power demand of the residences. Furthermore, it is revealed that for any number of target R-FCGSs, the IC has an advantage in the energy saving over a stand-alone operation of individual R-FCGSs without the power interchange.

Hybridization of training aircraft with real world flight profiles

2019 ◽  
Vol 91 (2) ◽  
pp. 353-365 ◽  
Author(s):  
Teresa Donateo ◽  
Roberto Totaro
Keyword(s):  
Power System ◽  
Electric Power ◽  
Real World ◽  
Weather Forecast ◽  
Forecast Model ◽  
Electric Power System ◽  
Power Demand ◽  
Content Type ◽  
Hybrid Electric ◽  
Modeling Strategy

Purpose The purpose of this paper is to analyze real-world flight data of a piston engine training aircraft collected from an internet-based radar service, along with wind data provided by a weather forecast model, and to use such data to design a hybrid electric power system. Design/methodology/approach The modeling strategy starts from the power demand imposed by a real-world wind-corrected flight profile, where speed and altitude are provided as functions of time, and goes through the calculation of the efficiency of the powertrain components when they meet such demand. Each component of the power system and, in particular, the engine and the propeller, is simulated as a black box with an efficiency depending on the actual working conditions. In the case of hybrid electric power system, the battery charging and discharging processes are simulated with the Shepherd model. Findings The variability of power demand and fuel consumption for a training aircraft is analyzed by applying the proposed methodology to the Piper PA-28-180 Cherokee, a very popular aircraft used for flight training, air taxi and personal use. The potentiality of hybridization is assessed by analyzing the usage of the engine over more than 90 flights. A tentative sizing of a hybrid electric power system is also proposed. It guarantees a fuel saving of about 5%. Originality/value The scientific contribution and the novelty of the investigation are related to the modeling methodology, which takes into account real-world flight conditions, and the application of hybridization to a training aircraft.

scholarly journals Energy-Saving and CO2-Emissions-Reduction Potential of a Fuel Cell Cogeneration System for Condominiums Based on a Field Survey

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6611
Author(s):  
Kazui Yoshida ◽  
Hom B. Rijal ◽  
Kazuaki Bohgaki ◽  
Ayako Mikami ◽  
Hiroto Abe
Keyword(s):  
Power Generation ◽  
Energy Consumption ◽  
Fuel Cell ◽  
Energy Saving ◽  
Electric Power ◽  
Water Use ◽  
Co2 Emission ◽  
Contribution Rate ◽  
Electric Power Generation ◽  
Cogeneration System

A residential cogeneration system (CGS) is highlighted because of its efficient energy usage on both the supplier and consumer sides. It generates electricity and heat simultaneously; however, there is insufficient information on the efficiency according to the condition of usage. In this study, we analysed the performance data measured by the home energy management system (HEMS) and the lifestyle data of residents in a condominium of 356 flats where fuel cell CGS was installed in each flat. The electricity generated by CGS contributed to an approximately 12% reduction in primary energy consumption and CO2 emission, and the rate of generation by the CGS in the electric power demand (i.e., contribution rate) was approximately 38%. The electricity generation was mainly affected by the use of electricity up to 4 MWh/household/year. Gas or water use also impacted electric power generation, with water use as the primary factor affecting the contribution rate. Electric power generation changes monthly, mainly based on the water temperature. From these results, we confirmed that a CGS has substantial potential to reduce energy consumption and CO2 emission in condominiums. Thus, it is recommended for installation of fuel cell CGS in existing and new buildings to contribute to the energy-saving target of the Japanese Government in the residential sector.

scholarly journals A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2472 ◽  
Author(s):  
Changyu Zhou ◽  
Guohe Huang ◽  
Jiapei Chen
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Power System ◽  
Electric Power ◽  
Clean Energy ◽  
Electric Power System ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Mixed Integer

In this study, a type-2 fuzzy chance-constrained fractional integrated programming (T2FCFP) approach is developed for the planning of sustainable management in an electric power system (EPS) under complex uncertainties. Through simultaneously coupling mixed-integer linear programming (MILP), chance-constrained stochastic programming (CCSP), and type-2 fuzzy mathematical programming (T2FMP) techniques into a fractional programming (FP) framework, T2FCFP can tackle dual objective problems of uncertain parameters with both type-2 fuzzy characteristics and stochastic effectively and enhance the robustness of the obtained decisions. T2FCFP has been applied to a case study of a typical electric power system planning to demonstrate these advantages, where issues of clean energy utilization, air-pollutant emissions mitigation, mix ratio of renewable energy power generation in the entire energy supply, and the displacement efficiency of electricity generation technologies by renewable energy are incorporated within the modeling formulation. The suggested optimal alternative that can produce the desirable sustainable schemes with a maximized share of clean energy power generation has been generated. The results obtained can be used to conduct desired energy/electricity allocation and help decision-makers make suitable decisions under different input scenarios.

scholarly journals A minimization model of the power shortage of electric power systems with regard to the restrictions on controlled sections

2021 ◽  
pp. 95-120
Author(s):  
Dmitry Iakubovsky ◽  
◽  
Dmitry Krupenev ◽  
Denis Boyarkin ◽  
◽  
...  
Keyword(s):  
Power Systems ◽  
Mathematical Models ◽  
Electric Power ◽  
Power Flow ◽  
Power Transmission ◽  
Electric Power Systems ◽  
Variable Number ◽  
Electric Power System ◽  
Active Power Flow ◽  
Adequacy Assessment

A steady trend towards the development of electric power systems leads to their continuous enlargement and sophistication. As a result, new ways of their control appear. In this regard, the existing models and complexes for adequacy assessment may work inadequately and ineffectively in terms of the obtained results adequacy. To assess the current state of the existing models and complexes, we reviewed and analyzed the domestic and foreign software and computer systems. In particular, we considered mathematical models of minimizing the power shortage. This work is based on the problem of modifying mathematical models of minimizing the power shortage used in adequacy assessment of the electric power systems of one of the complexes under consideration. As a modification of mathematical models, it is proposed to exclude the existing method of using the line capacities and start use correct accounting for the maximum permissible active power flow in controlled sections. The experimental part reflected in the paper concerns the testing of options for models to minimize the power shortage, as well as the proposed modifications on various systems, including those consisting of three and seven reliability zones with a variable number of controlled sections and power lines included in them. The results of the study have shown that the proposed modifications are efficient and can be used in the future. The authors also obtained the most adequate results in terms of the physical laws of electric power system operation due to the model of minimizing the power shortage with quadratic losses which takes into account the limitations of power transmission over controlled sections.

scholarly journals Robust Optimization for Electricity Generation

2020 ◽  
Author(s):  
Haoxiang Yang ◽  
David P. Morton ◽  
Chaithanya Bandi ◽  
Krishnamurthy Dvijotham
Keyword(s):  
Renewable Energy ◽  
Robust Optimization ◽  
Electric Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problem ◽  
Convex Relaxation ◽  
Electric Power System ◽  
Robust Convex Optimization ◽  
Robust Optimization Problem

We consider a robust optimization problem in an electric power system under uncertain demand and availability of renewable energy resources. Solving the deterministic alternating current (AC) optimal power flow (ACOPF) problem has been considered challenging since the 1960s due to its nonconvexity. Linear approximation of the AC power flow system sees pervasive use, but does not guarantee a physically feasible system configuration. In recent years, various convex relaxation schemes for the ACOPF problem have been investigated, and under some assumptions, a physically feasible solution can be recovered. Based on these convex relaxations, we construct a robust convex optimization problem with recourse to solve for optimal controllable injections (fossil fuel, nuclear, etc.) in electric power systems under uncertainty (renewable energy generation, demand fluctuation, etc.). We propose a cutting-plane method to solve this robust optimization problem, and we establish convergence and other desirable properties. Experimental results indicate that our robust convex relaxation of the ACOPF problem can provide a tight lower bound.

scholarly journals Hybrid Imperialist Competitive and Grey Wolf Algorithm to Solve Multiobjective Optimal Power Flow with Wind and Solar Units

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2891 ◽  
Author(s):  
Jalel Ben Hmida ◽  
Mohammad Javad Morshed ◽  
Jim Lee ◽  
Terrence Chambers
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Analysis ◽  
Electric Power System ◽  
Energy Integration ◽  
Grey Wolf ◽  
Optimal Power ◽  
Grey Wolf Algorithm

The optimal power flow (OPF) module optimizes the generation, transmission, and distribution of electric power without disrupting network power flow, operating limits, or constraints. Similarly to any power flow analysis technique, OPF also allows the determination of system’s state of operation, that is, the injected power, current, and voltage throughout the electric power system. In this context, there is a large range of OPF problems and different approaches to solve them. Moreover, the nature of OPF is evolving due to renewable energy integration and recent flexibility in power grids. This paper presents an original hybrid imperialist competitive and grey wolf algorithm (HIC-GWA) to solve twelve different study cases of simple and multiobjective OPF problems for modern power systems, including wind and photovoltaic power generators. The performance capabilities and potential of the proposed metaheuristic are presented, illustrating the applicability of the approach, and analyzed on two test systems: the IEEE 30 bus and IEEE 118 bus power systems. Sensitivity analysis has been performed on this approach to prove the robustness of the method. Obtained results are analyzed and compared with recently published OPF solutions. The proposed metaheuristic is more efficient and provides much better optimal solutions.

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