scholarly journals A Two-Stage Configuration Method of Integrated Community Energy System Considering Demand Response

2021 ◽  
Vol 252 ◽  
pp. 03011
Author(s):  
Jianfeng Yang ◽  
Tianxiang Xie ◽  
Chang Zhang ◽  
Jie Dong ◽  
Jianhao Zhang ◽  
...  
Keyword(s):  
Demand Response ◽  
Operating Cost ◽  
Energy System ◽  
Operating Efficiency ◽  
Maintenance Cost ◽  
Two Stage ◽  
Second Stage ◽  
Low Emission ◽  
Investment Cost ◽  
Annual Operating Cost

The integrated community energy system (ICES) has aroused considerable attention for its low emission and high operating efficiency. The existing configuration methods for ICES with multi-energy sectors ignored the controllable load. In this paper, a two-stage configuration method of ICES is developed to achieve the minimum annual investing and operating cost. At the first stage, the capacities of components in ICES are optimized to minimize the annual investment cost of ICES. At the second stage, the annual operating cost including the electricity and gas purchase costs and the component maintenance cost is minimized to satisfy the energy load. The controllable load under the time-of-use energy price in seasonal typical days is considered in the second stage. Relevant simulations are conducted to validate the effectiveness of the proposed configuration method for ICES. Considering the controllable load, comparative simulations illustrate that the proposed configuration method can significantly reduce the battery investment cost.

scholarly journals A Two-Stage Cooperative Dispatch Model for Power Systems Considering Security and Source-Load Interaction

2021 ◽  
Vol 13 (23) ◽  
pp. 13350
Author(s):  
Haiteng Han ◽  
Chen Wu ◽  
Zhinong Wei ◽  
Haixiang Zang ◽  
Guoqiang Sun ◽  
...  
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Renewable Energy Sources ◽  
Operating Cost ◽  
Multi Objective Optimization ◽  
Two Stage ◽  
Optimal Dispatch ◽  
Second Stage ◽  
The Relationship ◽  
Interactive Resources

In modern power systems with more renewable energy sources connected, the consideration of both security and economy becomes the key to research on power system optimal dispatch, especially when more participants from the source and load sides join in the interaction response activities. In this paper, we propose a two-stage dispatch model that contains a day-ahead multi-objective optimization scheduling sub-model that combines a hyper-box and hyper-ellipse space theory-based system security index in the first stage, and an intraday adjustment scheduling sub-model that considers active demand response (DR) behavior in the second stage. This model is able to quantitatively analyze the relationship between the security and economy of the system dispatch process, as well as the impacts of the interaction response behavior on the wind power consumption and the system’s daily operating cost. The model can be applied to the evaluation of the response mechanism design for interactive resources in regional power systems.

scholarly journals Strategies for Datacenters Participating in Demand Response by Two-Stage Decisions

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuling Li ◽  
Xiaoying Wang ◽  
Peicong Luo
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Smart Grids ◽  
Peak Load ◽  
Two Stage ◽  
The Sustainable Development ◽  
Second Stage ◽  
Potential Demand ◽  
Electricity Costs ◽  
Demand Response Programs

Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.

Two-stage flexible warranty decision-making considering downtime loss

2019 ◽  
Vol 234 (3) ◽  
pp. 527-535
Author(s):  
Rui Zheng ◽  
Chun Su ◽  
Yuqiao Zheng
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Service Cost ◽  
Decision Framework ◽  
Two Stage ◽  
Warranty Period ◽  
Second Stage ◽  
Warranty Service ◽  
Warranty Policies

Most existing warranty policies are rigid, and the downtime loss is also not taken into account. This study develops a two-stage decision framework to design flexible warranty policies, where the downtime loss is considered. In the first stage, by minimizing the warranty service cost, a fixed warranty policy is provided to determine the baseline of preventive maintenance’s times and effort. In the second stage, customers have three options to increase preventive maintenance times, preventive maintenance effort, or both of them, which results in three types of flexible warranty policies. The additional maintenance cost for the increased preventive maintenance times and/or preventive maintenance effort is paid by the customers. Besides, the flexible policies are optimized to minimize customer’s cost, which is the sum of the downtime loss and shared maintenance cost. A practical example is provided to illustrate the effectiveness of the proposed flexible warranty policies. The results indicate that compared with the fixed warranty policies, both the manufacturer and customers can benefit from the proposed flexible policies, especially when the downtime loss is substantial. Moreover, the proposed policy is more effective when the warranty period is longer.

scholarly journals Decision Problem on Imperfect Inspections Combined under Two-Stage Inspection Policy

2021 ◽  
Vol 11 (19) ◽  
pp. 9348
Author(s):  
Anna Jodejko-Pietruczuk
Keyword(s):  
Hydraulic Cylinder ◽  
Maintenance Cost ◽  
Testing Time ◽  
Effective Parameters ◽  
Two Stage ◽  
Simple Task ◽  
Inspection Method ◽  
Policy Model ◽  
Second Stage ◽  
Inspection Policy

Although one can presently observe great development in the methods for diagnosing conditions of technical systems, inspections which are not 100% accurate are still common in industry. If there are multiple available inspection methods which differ in accuracy of diagnosis, cost, or testing time, the answer for the question: which inspection method should be chosen is not a simple task. This paper addresses the problem and proposes a two-stage inspection policy model whose aim is to combine inspection methods that differ in their accuracy and cost features. The two-stage policy models that have been used so far in the literature assume that the second stage of an inspection is perfect, which is not always possible or profitable. For this reason, the mathematical model of the two-stage inspection policy with not-necessarily-perfect second stage is developed here, and its results are presented for the case study of diagnosing sealing in a hydraulic cylinder. The example proved that the application of mixed imperfect inspections could decrease maintenance cost, compared to the one-stage perfect inspection policy, by up to 35%. The paper also formulates a set of rules that support decision making while searching for cost-effective parameters of the two-stage policy. Their application is confirmed by a numerical example, which shows their potential in suboptimization of the proposed policy.

scholarly journals Selection of Best Power Supply Source for Telecom Towers in Remote Areas

2020 ◽  
Vol 5 (5) ◽  
pp. 913-925
Author(s):  
Shwetank Avikal ◽  
Rahul Singhal ◽  
Rajat Sajwan ◽  
Rahul Kumar Tiwari ◽  
Rohit Singh
Keyword(s):  
Power Supply ◽  
Fuzzy Ahp ◽  
Operating Cost ◽  
Energy System ◽  
Maintenance Cost ◽  
Diesel Generator ◽  
Supply Source ◽  
Remote Areas ◽  
Power Supply Source ◽  
Diesel Generators

Installation of telecom towers in remote areas especially in developing countries like India is a major problem for telecom industries because of the unavailability of reliable power supply. The grid supply is not regular in these countries and up to some extent, they are dependent on diesel generators for power supply. But these diesel generators have some major issues such as high operating cost due to high cost of fuel, transportation cost of fuel, high maintenance cost, and these diesel generators also emits pollution to the environment. In presented work, an approach has been proposed for telecom companies for providing power supply to their telecom towers. An economic cost analysis has been proposed by considering various criteria such as cost, air & noise pollution and reliability, etc. Some power supply alternatives including unconventional and hybrid of conventional and unconventional alternatives have been compared to find the solution such as diesel-powered telecom towers, solar powered telecom towers, and their hybrids. The main objective of this work is to provide a reliable, cost effective and environment friendly Remote Area Power Supply (RAPS) system for a particular site in India (Uttar Pradesh). A number of criteria are involved in discussed problem in order to select an effective power supply source. Therefore, the problem has been considered as a Multi Criteria Decision Making (MCDM) problem. To select the best alternative, a Fuzzy AHP and TOPSIS based approach has been proposed. Fuzzy AHP (Analytic Hierarchy process) has been used for calculating the weightage of criteria and the concept of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) has been applied for ranking the alternatives. The results give assured reliability and sustainability for remote areas using a solar photovoltaic (PV)-diesel generator hybrid energy system.

scholarly journals Benchmarking Engineering, Procurement and Construction (EPC) Power Plant Projects by Means of Series Two-Stage DEA

Electricity ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Ioannis E. Tsolas
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Combined Cycle ◽  
Operating Efficiency ◽  
Data Envelopment ◽  
Power Sector ◽  
Two Stage ◽  
Second Stage ◽  
Ex Ante ◽  
Open Cycle

A lot of companies in the power sector use Engineering, Procurement, and Construction (EPC) contracts for complex infrastructure projects such as power plants. This paper presents a series two-stage data envelopment analysis (DEA) approach for the ex ante benchmarking of EPC power plant projects. The current study aims to improve over single-stage DEA and evaluate the efficiency of a group of twelve domestic (located in Greece) and international natural gas-fired power plant projects of different technologies (combined cycle power plant (CCPP) projects with single and multi-shaft configuration, and open cycle power plant (OCPP) projects) by employing a series two-stage DEA model. In the first stage, performance of the EPC mode is evaluated, whereas in the second stage the plant annual operational efficiency is assessed. In the light of the results, there is a lower level of performance in the EPC mode than in operating efficiency. The OCPP projects have the best operating efficiency, whereas they are ranked in-between the CCPP projects with single and multi-shaft configuration in EPC mode performance.

scholarly journals Optimal scheduling of building integrated energy system based on demand response

2020 ◽  
Vol 185 ◽  
pp. 01068
Author(s):  
Mengju Wei ◽  
Yang Yang ◽  
Mengjin Hu ◽  
Yongli Wang ◽  
Siyi Tao ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Cloud Model ◽  
Operating Cost ◽  
Energy System ◽  
Model Particle ◽  
On Demand ◽  
Integrated Energy System ◽  
Building Level ◽  
Particle Group

With the development of renewable energy technology, integrating a variety of renewable energy integrated energy systems can effectively solve the problem of optimizing the scheduling of buildings with high energy consumption and fast growth rate. Based on the modeling and analysis of various energy equipment in the system, the integrated energy system of building buildings, based on the demand response compensation price, with the lowest construction operating cost as the goal function, establishes the optimization scheduling model of building-level integrated energy system based on demand response, and uses the particle group algorithm based on cloud model improvement to optimize the solution of the model. The study is introduced for simulation to compare the two different modes of participation in demand response, and the optimal performance of cloud model particle group algorithm and elementary particle group algorithm. The results show that the cloud model particle group algorithm model based on demand response can effectively save the operating cost of the building-level integrated energy system, and reduce the power grid side load peak and valley difference.

scholarly journals Optimal Operation Of Integrated Energy System Considering Demand Response

2021 ◽  
Vol 2087 (1) ◽  
pp. 012017
Author(s):  
Yan Liang ◽  
Yao Wang ◽  
Hongli Liu ◽  
Peng Wang ◽  
Yongming Jing ◽  
...  
Keyword(s):  
Demand Response ◽  
Operating Cost ◽  
Energy System ◽  
Optimal Operation ◽  
Adaptive Genetic Algorithm ◽  
Load Matching ◽  
Integrated Energy Systems ◽  
Cost Of Energy ◽  
Integrated Energy System ◽  
System Operating

Abstract Due to the high cost of energy storage part in traditional integrated energy systems, the demand response effect is poor. The paper proposes electrolytic water hydrogen production technology and applies it to the optimal operation of integrated energy system. By optimizing the operating cost of the system through adaptive genetic algorithm, we show that when the load matching degree was increased from 50% to 70%, the system operating cost was reduced by about 15.8%, and the carbon displacement was decreased by about 35%. System operating costs, carbon emissions, and the amount of electrolytic water systems involved in the demand response have all decreased.

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