Feasibility Analysis of Demand Response Transport (DRT) over Route Buses Using Operating Cost Functions

2021 ◽  
Author(s):  
Ki-Jun Park ◽  
Hun-Young Jung ◽  
Sang-Min Jeon
Keyword(s):  
Demand Response ◽  
Operating Cost ◽  
Feasibility Analysis ◽  
Cost Functions

Energy management of a microgrid using demand response strategy including renewable uncertainties

2021 ◽  
Vol 22 (1) ◽  
pp. 85-100
Author(s):  
Suchitra Dayalan ◽  
Rajarajeswari Rathinam
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Demand Response ◽  
Effective Means ◽  
Operating Cost ◽  
Energy Resources ◽  
Response Strategy ◽  
Distributed Energy ◽  
Real Time Control ◽  
Minimum Operating

Abstract Microgrid is an effective means of integrating multiple energy sources of distributed energy to improve the economy, stability and security of the energy systems. A typical microgrid consists of Renewable Energy Source (RES), Controllable Thermal Units (CTU), Energy Storage System (ESS), interruptible and uninterruptible loads. From the perspective of the generation, the microgrid should be operated at the minimum operating cost, whereas from the perspective of demand, the energy cost imposed on the consumer should be minimum. The main key in controlling the relationship of microgrid with the utility grid is managing the demand. An Energy Management System (EMS) is required to have real time control over the demand and the Distributed Energy Resources (DER). Demand Side Management (DSM) assesses the actual demand in the microgrid to integrate different energy resources distributed within the grid. With these motivations towards the operation of a microgrid and also to achieve the objective of minimizing the total expected operating cost, the DER schedules are optimized for meeting the loads. Demand Response (DR) a part of DSM is integrated with MG islanded mode operation by using Time of Use (TOU) and Real Time Pricing (RTP) procedures. Both TOU and RTP are used for shifting the controllable loads. RES is used for generator side cost reduction and load shifting using DR performs the load side control by reducing the peak to average ratio. Four different cases with and without the PV, wind uncertainties and ESS are analyzed with Demand Response and Unitcommittment (DRUC) strategy. The Strawberry (SBY) algorithm is used for obtaining the minimum operating cost and to achieve better energy management of the Microgrid.

scholarly journals An Energy Management Optimization Method for Community Integrated Energy System Based on User Dominated Demand Side Response

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4398
Author(s):  
Yiqi Li ◽  
Jing Zhang ◽  
Zhoujun Ma ◽  
Yang Peng ◽  
Shuwen Zhao
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Value At Risk ◽  
Operating Cost ◽  
Optimization Method ◽  
Conditional Value At Risk ◽  
Demand Side ◽  
Scheduling Model ◽  
Management Optimization ◽  
Demand Side Response

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users’ willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department.

Gas Compressor Service With Turbo Compressors

2004 ◽  
Author(s):  
Sidney Pereira dos Santos
Keyword(s):  
Operating Cost ◽  
Gas Pipeline ◽  
Feasibility Analysis ◽  
Economic Approach ◽  
Compressor Station ◽  
Centrifugal Compressors ◽  
Great Opportunity ◽  
Service Contracts ◽  
Gas Compression ◽  
Capital Intensive

Gas pipeline projects are capital intensive and normally are developed under scenarios of uncertainty. Such uncertainties vary from closing take-or-pay, ship-or-pay or delivery-or-pay agreements to those uncertainties related to the acquisition of equipments, material and construction and assembling contracts. Natural gas compression service contracts with compressor station using gas motors and reciprocating compressors have been widely adopted at PETROBRAS as economically feasible against holding the stations as part of the pipeline asset as well as providing an effective approach to mitigate risks inherent to the gas business and associated to the compressor stations. Although compression service contracts with turbo compressors (gas turbine drivers and centrifugal compressors) have not yet been accomplished at PETROBRAS for gas pipeline projects, studies and preliminaries discussions shows that, taken into consideration certain relevant aspects, they will also present great opportunity to be adopted and will generate the same advantages already perceived for the compression service contracts with stations that uses gas motor drivers and reciprocation compressors. This paper has the objective of presenting an economic approach and a business model addressing the main points that must be considered while doing feasibility analysis between the alternatives of holding property of the compression station asset against the opportunity of having a compression service contract as operating cost for the project. Questions such as how to address depreciation, overhaul costs and tailor made equipment, such as centrifugal compressors, are raised and answered.

scholarly journals Solving optimal generation scheduling problem of microgrid using teaching learning based optimization algorithm

2020 ◽  
Vol 17 (3) ◽  
pp. 1632
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Demand Response ◽  
Operating Cost ◽  
Optimal Scheduling ◽  
Energy Resources ◽  
Successful Implementation ◽  
Scheduling Problem ◽  
Solar Pv ◽  
Teaching Learning Based Optimization ◽  
Diesel Generators ◽  
Teaching Learning

<p>This paper proposes a new optimal scheduling methodology for a Microgrid (MG) considering the energy resources such as diesel generators, solar photovoltaic (PV) plants, wind farms, battery energy storage systems (BESSs), electric vehicles (EVs) and demand response (DR). The penetration level of renewable and sustainable energy resources (i.e., wind, solar PV energy, geothermal and ocean energy) in power generation systems is increasing. In this work, the EVs and storage are used as flexible DR sources and they can be combined with DR to improve the flexibility of MG. Various uncertainties exist in the MGs due to the intermittent/uncertain nature of renewable energy resources (RERs) such as wind and solar PV power outputs. In this paper, these uncertainties are modeled by using the probability analysis. In this paper, the optimal scheduling problem of MG is solved by minimizing the total operating cost (TOC) of MG. The TOC minimization objective is formulated by considering the cost due to power exchange between main grid and MG, diesel generators, wind, solar PV units, EVs, BESSs, and DR. The successful implementation of optimal scheduling of MG requires the widespread use of demand response and EVs. In this paper, teaching-learning-based optimization (TLBO) algorithm is used to solve the proposed optimization problem. The simulation studies are performed on a test MG by considering all the components of MG.</p>

scholarly journals Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2810 ◽  
Author(s):  
Keon Baek ◽  
Woong Ko ◽  
Jinho Kim
Keyword(s):  
Demand Response ◽  
Management System ◽  
Reference Model ◽  
Storage System ◽  
Operating Cost ◽  
Energy Resource ◽  
Residential Building ◽  
Mixed Integer ◽  
Distributed Energy ◽  
Proposed Model

This study proposes optimal day-ahead demand response (DR) participation strategies and distributed energy resource (DER) management in a residential building under an individual DR contract with a grid-system operator. First, this study introduces a DER management system in the residential building for participation to the day-ahead DR market. The distributed photovoltaic generation system (PV) and energy-storage system (ESS) are applied to reduce the electricity demand in the building and sell surplus energy on the grid. Among loads in the building, lighting (LTG) and heating, ventilation, and air conditioning (HVAC) loads are included in the DR program. In addition, it is assumed that a power management system of an electric vehicle (EV) charging station is integrated the DER management system. In order to describe stochastic behavior of EV owners, the uncertainty of EV is formulated based on their arrival and departure scenarios. For measuring the economic efficiency of the proposed model, we compare it with the DER self-consuming operation model without DR participation. The problem is solved using mixed integer linear programming to minimize the operating cost. The results in summer and winter are analyzed to evaluate the proposed algorithm’s validity. From these results, the proposed model can be confirmed as reducing operation cost compared to the reference model through optimal day-ahead DR capacity bidding and implementation.

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 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 Optimal Operation of Microgrid considering Renewable Energy Sources, Electric Vehicles and Demand Response

2019 ◽  
Vol 87 ◽  
pp. 01007 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Electric Vehicles ◽  
Hybrid System ◽  
Demand Response ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Operating Cost ◽  
Energy Systems ◽  
Optimal Operation ◽  
Solar Pv ◽  
The Cost

This paper proposes a new optimal operation of Microgrids (MGs) in a distribution system with wind energy generators (WEGs), solar photovoltaic (PV) energy systems, battery energy storage (BES) systems, electric vehicles (EVs) and demand response (DR). To reduce the fluctuations of wind, solar PV powers and load demands, the BES systems and DR are utilized in the proposed hybrid system. The detailed modeling of WEGs, solar PV units, load demands, BES systems and EVs has been presented in this paper. The objective considered here is the minimization of total operating cost of microgrid, and it is formulated by considering the cost of power exchange between the main power grid and microgrid, cost of wind and solar PV energy systems, cost of BES systems, EVs and the cost due to the DR in the system. Simulations are performed on a test microgrid, and they are implemented using GAMS software. Various case studies are performed with and without considering the proposed hybrid system.

Research on Demand Side Response System of Electricity Price Under Electricity Market Incentive Mechanism

2021 ◽  
Author(s):  
Fu Xianyu ◽  
Zhou Hongmei ◽  
Qi-jie Jiang ◽  
Ke Fan
Keyword(s):  
Power System ◽  
Demand Response ◽  
Electricity Market ◽  
Incentive Mechanism ◽  
Operating Cost ◽  
Electricity Price ◽  
Demand Side ◽  
Peak Shaving ◽  
Optimal Dispatch ◽  
Grid Operation

Aiming at the traditional day-ahead dispatching scheme of power generation, the paper proposes a power system security optimization dispatching model that considers the demand response of electricity prices under the electricity market incentive mechanism. Based on the peak and valley time-of-use electricity price, the paper establishes an incentive compensation mechanism to encourage users to be active. Participating in demand-side resource scheduling makes the effect of “peak shaving and valley filling” more pronounced. Simultaneously, to rationally configure the reserve capacity of grid operation, the system incorporates the expected power outage loss into the proposed model to ensure the grid operation safety. The analysis of calculation examples based on IEEE24 nodes shows that the power optimal dispatch model proposed in the paper considering demand response and expected outage loss can reduce the operating cost of the power grid under the premise of ensuring a certain level of reliability and realize the economy of the power system in the market environment and safe operation.

scholarly journals An Optimal Energy Optimization Strategy for Smart Grid Integrated with Renewable Energy Sources and Demand Response Programs

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5718
Author(s):  
Kalim Ullah ◽  
Sajjad Ali ◽  
Taimoor Ahmad Khan ◽  
Imran Khan ◽  
Sadaqat Jan ◽  
...  
Keyword(s):  
Demand Response ◽  
Optimization Model ◽  
Carbon Emission ◽  
Renewable Energy Sources ◽  
Operating Cost ◽  
Energy Sources ◽  
Optimization Strategy ◽  
Model Based ◽  
Demand Response Programs ◽  
Operation Cost

An energy optimization strategy is proposed to minimize operation cost and carbon emission with and without demand response programs (DRPs) in the smart grid (SG) integrated with renewable energy sources (RESs). To achieve optimized results, probability density function (PDF) is proposed to predict the behavior of wind and solar energy sources. To overcome uncertainty in power produced by wind and solar RESs, DRPs are proposed with the involvement of residential, commercial, and industrial consumers. In this model, to execute DRPs, we introduced incentive-based payment as price offered packages. Simulations are divided into three steps for optimization of operation cost and carbon emission: (i) solving optimization problem using multi-objective genetic algorithm (MOGA), (ii) optimization of operating cost and carbon emission without DRPs, and (iii) optimization of operating cost and carbon emission with DRPs. To endorse the applicability of the proposed optimization model based on MOGA, a smart sample grid is employed serving residential, commercial, and industrial consumers. In addition, the proposed optimization model based on MOGA is compared to the existing model based on multi-objective particle swarm optimization (MOPSO) algorithm in terms of operation cost and carbon emission. The proposed optimization model based on MOGA outperforms the existing model based on the MOPSO algorithm in terms of operation cost and carbon emission. Experimental results show that the operation cost and carbon emission are reduced by 24% and 28% through MOGA with and without the participation of DRPs, respectively.

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