• Title/Summary/Keyword: Power demand

Search Result 2,563, Processing Time 0.031 seconds

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

  • Zeng, Bo;Zhang, Jianhua;Zhang, Yuying;Yang, Xu;Dong, Jun;Liu, Wenxia
    • Journal of Electrical Engineering and Technology
    • /
    • v.9 no.2
    • /
    • pp.433-440
    • /
    • 2014

  • In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

  • https://doi.org/10.5370/JEET.2014.9.2.433 인용 PDF KSCI KPUBS HTML

Power Trading System through the Prediction of Demand and Supply in Distributed Power System Based on Deep Reinforcement Learning (심층강화학습 기반 분산형 전력 시스템에서의 수요와 공급 예측을 통한 전력 거래시스템)

  • Lee, Seongwoo;Seon, Joonho;Kim, Soo-Hyun;Kim, Jin-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.21 no.6
    • /
    • pp.163-171
    • /
    • 2021

  • In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

  • https://doi.org/10.7236/JIIBC.2021.21.6.163 인용 PDF KSCI HTML

Analysis of the Impact of the 8th Basic Plan for Long-term Electricity Supply and Demand on the District Heating Business Through Optimal Simulation of Gas CHP (가스 열병합발전 최적 시뮬레이션 분석을 통한 집단에너지 사업자에 미치는 8차 전력 수급계획의 영향 분석)

  • Kim, Young Kuk;Oh, Kwang Min;Kim, Lae Hyun
    • Korean Chemical Engineering Research
    • /
    • v.56 no.5
    • /
    • pp.655-662
    • /
    • 2018

  • To respond effectively to climate change following the launch of the new climate system, the government is seeking to expand the use of distributed power resources. Among them, the district heating system centered on Combined Heat and Power (CHP) is accepted as the most realistic alternative. On the other hand, the government recently announced the change of energy paradigm focusing on eco-friendly power generation from the base power generation through $8^{th}$ Basic Plan for Long-term Electricity Supply and Demand(BPE). In this study, we analyzed the quantitative effects of profit and loss on the CHP operating business by changing patterns of the heat production, caused by the change of energy paradigm. To do this, the power market long-term simulation was carried out according to the $7^{th}$ and $8^{th}$ BPE respectively, using the commercialized power market integrated analysis program. In addition, the CHP operating model is organized to calculate the power and heat production level for each CHP operation mode by utilizing the operating performance of 830MW class CHP in Seoul metropolitan area. Based on this, the operation optimization is performed for realizing the maximum operating profit and loss during the life-cycle of CHP through the commercialized integrated energy optimization program. As a result, it can be seen that the change of the energy paradigm of the government increased the level of the ordered power supply by Korean Power Exchange(KPX), decreased the cost of the heat production, and increased the operating contribution margin by 90.9 billion won for the 30 years.

  • https://doi.org/10.9713/kcer.2018.56.5.655 인용 PDF KSCI