Optimal Power Generation Unit Sizing for Combined Heating and Power Systems With Uncertain Loads and Fuel/Electricity Prices

2011 ◽  
Author(s):  
Aaron Smith ◽  
Kyungtae Yun ◽  
Robert Thomas ◽  
Rogelio Luck
Keyword(s):  
Power Systems ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Computational Effort ◽  
Mixed Integer ◽  
Weather Data ◽  
Optimal Sizing ◽  
Electricity Cost ◽  
Analytical Scheme

An optimal sizing method is developed in this work based on an analytical scheme for determining optimal operation decisions. Using the analytic optimal operation scheme allows for a more thorough optimal sizing method because of the minimal computational effort required as compared to mixed integer programming approaches. For example, an optimal sizing method based on this approach can more feasibly consider several years of weather data and the range of likely fuel/electricity costs for the term of operation of the PGU. The optimal sizing method in this work takes advantage of this efficient optimal operation scheme and provides a robust optimal solution with respect to weather and fuel/electricity cost uncertainty. A case study of a medium sized office building is carried out by testing the algorithm for a range of 20 commercially available diesel engine PGUs.

scholarly journals Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Hafiz Abd ul Muqeet ◽  
Hafiz Mudassir Munir ◽  
Aftab Ahmad ◽  
Intisar Ali Sajjad ◽  
Guang-Jun Jiang ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Solar Irradiance ◽  
Distribution System ◽  
Energy Demand ◽  
Mathematical Problem ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Proposed Model

Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid (µG). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

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.

Technical and Economical Assessment of using Static Compensators for Improving Power Quality in Distribution Power Systems

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Reza Tajik
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Low Cost ◽  
Optimal Solution ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Objective Functions ◽  
Dynamic Voltage Restorer ◽  
Multi Objective ◽  
Hybrid Devices

Nowadays, various issues regarding the power quality have been widely considered. Regarding to the progress made in power electronics in recent years, the best way to improve the reliability of reducing voltage deviations, reducing losses, and generally providing high quality to consumers is to use custom power devices (CPDs). Series, parallel, or hybrid devices come from a subset of CPDs such as a dynamic voltage restorer, distribution static compensator, and unified power quality conditioner. In this work, the purpose of place these devices are to achieve various goals of improving power quality and reducing system costs. To achieve these goals, at first, the problem of single-objective optimization for each of the objective functions was solved separately. After determining the optimal value of each of the objective functions, the fuzzy membership functions for each of the objective functions were suitably optimized for each objective function. A mixed integer genetic algorithm was used to find the optimal answer to this multi-objective problem. The simulation results show that the proposed algorithm has worked well to find the optimal solution. The results of multi-objective planning proposed in this study show that with proper planning, it can be done at a low cost and even with a relatively high profit to cost and with the proper place of CPDs, to solve issues related to power quality issues in distribution networks.

scholarly journals Optimal load dispatch strategies for a hybrid system using renewable energy sources

2021 ◽  
Vol 897 (1) ◽  
pp. 012015
Author(s):  
Ronald Ayala Ramírez ◽  
Javier Tenesaca Chacaguasay ◽  
Juan Lata García
Keyword(s):  
Power Systems ◽  
Renewable Energy Sources ◽  
Optimal Operation ◽  
Diesel Generator ◽  
Hybrid Power Systems ◽  
Software Optimization ◽  
Hybrid Microgrid ◽  
Cost Of Energy ◽  
Optimal Load

Abstract Recently, the idea of hybrid power systems (HES) has attracted interest for the electrification of isolated or energy efficient areas. This document examines the modelling and optimal dimensions of a hybrid microgrid using different dispatch strategies. The sizing of the HES components such as Photovoltaic panels, Batteries, Inverter, a Diesel generator has been optimized by three strategies: (i) load tracking, (ii) cycle load, and (iii) combined dispatch. The location of the case study is in a rural community in Ecuador whose load profile is 17 kW. By utilizing HOMER software, optimization for the HES was achieved with the Combined Dispatch strategy (CD) which presented the minimum levels in the net annual cost (NPC), initial capital, levelized cost of energy (LCOE) of $ 90,073.10, $ 21,208 and $ 0.2016 / kWh, respectively. The conclusions offer a guide to consider the resources and generation combination essential for the optimal operation of an island microgrid with different dispatch scenarios.

scholarly journals DC-Microgrid Operation Planning for an Electric Vehicle Supply Infrastructure

2019 ◽  
Vol 9 (13) ◽  
pp. 2687 ◽  
Author(s):  
Benedetto Aluisio ◽  
Sergio Bruno ◽  
Luca De Bellis ◽  
Maria Dicorato ◽  
Giuseppe Forte ◽  
...  
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Operation Planning ◽  
Energy Storage Devices ◽  
Dc Microgrid ◽  
Charging Station ◽  
Smart Charging ◽  
Non Linear

The integration of electric vehicles (EVs) in power systems can be encouraged by charging station diffusion. These stations can perform smart charging processes, and can take advantage of the involvement of distributed generation sources in a microgrid framework. Furthermore, since photovoltaic batteries and EVs are sources based on direct current (DC), the realization of a DC microgrid structure is promising, though challenging. In this paper, a mixed-integer linear procedure for determining optimal operation planning of a DC-based electric vehicle supply infrastructure is proposed. The procedure aims at optimizing daily operational costs, based on forecast of photovoltaic production and EV exploitation. Peculiar aspects of energy storage devices and of the DC microgrid framework are accounted for through a non-linear iterative procedure. The proposed approach is applied to a test DC microgrid on different operation days and its effectiveness is compared to non-linear formulation solved by means of a genetic algorithm.

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 A Dynamic Optimization Strategy for the Operation of Large Scale Seawater Reverses Osmosis System

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Aipeng Jiang ◽  
Jian Wang ◽  
Wen Cheng ◽  
Changxin Xing ◽  
Shu Jiangzhou
Keyword(s):  
Finite Element ◽  
Dynamic Model ◽  
Large Scale ◽  
Optimal Solution ◽  
Differential Algebraic Equations ◽  
Optimal Operation ◽  
Algebraic Equations ◽  
Optimization Strategy ◽  
Storage Tanks

In this work, an efficient strategy was proposed for efficient solution of the dynamic model of SWRO system. Since the dynamic model is formulated by a set of differential-algebraic equations, simultaneous strategies based on collocations on finite element were used to transform the DAOP into large scale nonlinear programming problem named Opt2. Then, simulation of RO process and storage tanks was carried element by element and step by step with fixed control variables. All the obtained values of these variables then were used as the initial value for the optimal solution of SWRO system. Finally, in order to accelerate the computing efficiency and at the same time to keep enough accuracy for the solution of Opt2, a simple but efficient finite element refinement rule was used to reduce the scale of Opt2. The proposed strategy was applied to a large scale SWRO system with 8 RO plants and 4 storage tanks as case study. Computing result shows that the proposed strategy is quite effective for optimal operation of the large scale SWRO system; the optimal problem can be successfully solved within decades of iterations and several minutes when load and other operating parameters fluctuate.

scholarly journals Hybrid model to design a distribution network in contract farming

DYNA ◽  
2019 ◽  
Vol 86 (208) ◽  
pp. 102-109 ◽  
Author(s):  
Rafael Granillo-Macias ◽  
Isidro Jesus Gonzalez Hernandez ◽  
Jose Luis Martinez-Flores ◽  
Santiago Omar Caballero-Morales ◽  
Elias Olivarez-Benitez
Keyword(s):  
Hybrid Model ◽  
Programming Model ◽  
Distribution Network ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Problem ◽  
Contract Farming ◽  
The Impact ◽  
Distribution Cost

This paper suggests a hybrid model to solve a distribution problem incorporating the impact of uncertainty in the solution. The model combines the deterministic approach and the simulation including stochastic variables such as harvest yield, loss risk and penalties/benefits to design a distribution network with the minimal cost. Through a case study that includes farmers, hubs and malt producers in the supplying chain of barley in Mexico, nine possible scenarios were analyzed to plan and distribute the harvested grain based on contract farming. This approach gets an optimal solution through an iterative process simulating the suggested solution by a mixed-integer linear programming model under uncertain conditions. The results show the convenience of maintaining the operation between four and five hubs depending on the possible scenario; besides, the variation of the levels of the barley producers’ capacities are key elements in the planning to minimize the distribution cost throughout the suggested chain

A Possibility Approach for the Single Item Lot Sizing Problem with Fuzzy Parameters

2016 ◽  
pp. 100-132
Author(s):  
Manoj Kumar ◽  
Jyoti Raman ◽  
Priya Singh
Keyword(s):  
Lot Sizing ◽  
Fuzzy Model ◽  
Optimal Solution ◽  
Unit Price ◽  
Mixed Integer ◽  
Inventory Planning ◽  
Single Item ◽  
Lot Sizing Problem ◽  
Fuzzy Parameters

The main objective of this chapter is to deal with a single item lot sizing problem with fuzzy parameters, which is called the fuzzy single item lot sizing problem (F-SILSP). Since F-SILSP does not meet the crisp deterministic assumption, it cannot be solved by traditional mathematical programming. In this chapter, the possibility approach is chosen to convert the fuzzy model to be an equivalent crisp single item lot sizing problem (EC-SILSP). The equivalent crisp model from this transformation procedure is in the form of mixed integer linear programming (MILP). It can be solved by traditional solver to find an optimal solution for each pre-specified possibility level. A numerical example with both trapezoidal and triangular fuzzy parameters is illustrated to demonstrate that an equivalent crisp model can be used. In addition, the equivalent crisp model is employed in inventory planning in a case study of inventory planning for bituminous coal with trapezoidal fuzzy demand and triangular fuzzy unit price in a power plant of an example petrochemical company (Supreme Petro, India).

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