Managing and Minimizing Cost of Energy in Virtual Power Plants in the Presence of Plug-in Hybrid Electric Vehicles Considering Demand Response Program

Barati, Hassan,Ashir, Farshid The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.2

Virtual power plants can be regarded as systems that have entered the network after restructure of power systems. In fact, these plants are a set of consumers capable of consuming and generating power. In response to widespread implementation of plug-in hybrid electric vehicles, further investigation of energy management in this type of power plants seems to be of great value. In effect, these vehicles are able to receive and inject power from/into the network. Hence, study of the effects of these vehicles on management of virtual power plants seems to be illuminative. In this paper, management of power consumption/generation in virtual power plants has been investigated in the presence of hybrid electric vehicles. The objective function of virtual power plants problem management is to minimize the overall costs including not only the costs of energy production in power generation units, fuels, and degradation of batteries of vehicles, but also the costs of purchasing electricity from the network. Furthermore, the constraints on the operational of plants, loads and hybrid vehicles, level of penalty for greenhouse gas emissions ($CO_2$ and $NO_x$) produced by power plants and vehicles, and demand response to the immediate price of market have all been attended to in the present study. GAMS/Cplex software system and sample power system have been employed to pursue computer implementation and simulation.

최소 출력변동성을 갖는 가상발전소 구성을 위한 분산형 재생에너지원의 최적 조합 방법

최어진,김종규,한혜승,김승완 대한전기학회 2020 전기학회논문지 Vol.69 No.12

Non-dispatchable distributed renewable energy sources, such as solar and wind generator, have large uncertainty and variability. Because of the nature, when an aggregator participates in the market as the form of virtual power plant, several problems may take place. For example, if less or excess generation is occurred, a penalty for deviation may be imposed to the virtual power plant. This penalty may negatively affect the profit of virtual power plant. There are two approaches to handle this problem. One is reducing forecasting errors in an operation stage and another is minimizing output variance when configuring a portfolio for virtual power plant in a planning stage. This work would propose a way of finding optimal combination of distributed renewable energy sources for configuration of virtual power plant with minimum output variance. It is expected that VPP can reduce the market risk using the proposed technique from this study.

분산발전자원을 활용한 가상발전소 기반 기술의 전력시장 참여 방안에 대한 연구

이윤환(Yun-Hwan Lee) 대한전기학회 2016 전기학회논문지 P Vol.65 No.2

A virtual power plant (VPP) technology is a cluster of distributed generation installations. VPP system is that integrates several types of distributed generation sources, so as to give a reliable overall power supply. Virtual power plant systems play a key role in the smart grids concept and the move towards alternative sources of energy. They ensure improved integration of the renewable energy generation into the grids and the electricity market. VPPs not only deal with the supply side, but also help manage demand and ensure reliability of grid functions through demand response (DR) and other load shifting approaches in real time. In this paper, utilizing a variety of distributed generation resources(such as emergency generator, commercial generator, energy storage device), activation scheme of the virtual power plant technology. In addition, through the analysis of the domestic electricity market, it describes a scheme that can be a virtual power plant to participate in electricity market. It attempts to derive the policy support recommendation in order to obtain the basics to the prepared in position of power generation companies for the commercialization of virtual power plant.

Approaches to Heuristic & Quantitative Analysis of Power Plant Equipment & Structure Layout Design based on Virtual Reality

Kwang Rak Seo(서광락) 대한인간공학회 2021 대한인간공학회 학술대회논문집 Vol.2021 No.11

The aim of this study is to drive the optimal design through various quantified alternatives for equipment and structure layout design of a Nuclear Power Plant, which are implemented in virtual reality. Currently, only the importance of design criteria for each design alternative is considered in the comparison of the layout design alternatives. If the priorities between design standards are considered here, more optimal design alternatives can be derived. In addition, comparisons that require differentiation in detail between designs, such as comparison of design alternatives, make it possible to heuristically discriminate differences in design details if realistic immersive virtual reality technology is applied. In order to derive the relationship between design criteria for each design alternative, a 5-step process, which is an easy quality function deployment (QFD) technique, was applied to improve design quality; 1) Design criteria(requirements), 2) Design importance, 3) Design alternatives, 4) Correlation table, 5) Design alternative priority. Through this process, the priorities of the major design criteria were analyzed, and the relationship with the design alternatives according to the design criteria was derived. In addition, the appropriateness of the job of plant staffs during construction and maintenance was additionally considered in the design criteria through the heuristic analysis of virtual reality space. As a result of deriving priorities according to the degree of relevance between design alternatives to design criteria by heuristic quantitative analysis, the importance of user’s workspace and design interference was high among the three design alternatives, so design alternative 3 was selected as the optimal alternative. The heuristic quantitative analysis method can consider the suitability of the plant staff’s job within the layout design, and since it is based on realistic and immersive virtual/augmented reality, the establishment of a digital power plant model must be preceded. In addition, it is expected that this analysis method can be applied to the alternative design review for changing the design of the power plant equipment and structures at the design stage according to the degree of implementation of the digital power plant model.

에너지전환 정책하에 전기차 수요자원의 경제적 가치 분석: 9차 전력수급계획 중심으로

전우영 ( Wooyoung Jeon ),조상민 ( Sangmin Cho ),조일현 ( Ilhyun Cho ) 한국환경경제학회·한국자원경제학회(구 한국환경경제학회) 2021 자원·환경경제연구 Vol.30 No.2

에너지전환 정책의 가속화로 변동성 재생에너지가 가파르게 증가하면서 계통수용비용이 빠르게 상승하고 있다. 변동성 재생에너지 증가는 기존 전통적 발전자원의 이용률을 하락시켜서 전력공급에 비효율성을 가중시키는데 이에 대한 해결책으로 수요자원이 주목받고 있다. 본 연구에서는 수요자원 중 큰 잠재력을 가지고 있는 전기차 수요가 재생발전에 대한 유연성 자원으로 활용될 경우 전력공급비용을 얼마나 경감시킬 수 있는지 9차 전력수급계획을 반영하여 분석하였다. 분석모형으로 재생발전의 확률적 특성을 사실적으로 반영할 수 있는 확률적 전력시스템 최적화 모형을 적용해서 재생에너지가 유발하는 비용과 전기차 수요자원의 편익을 분석하였다. 분석결과 계시별 요금제보다 가상발전소 기반의 직접제어방식이 편익이 더 높고, 발전구성에서 재생에너지의 비중이 높아질수록 편익이 더 높아지는 것으로 나타났다. 전기차 수요자원의 구현비용인 중개사업자 수수료와 배터리마모비용을 고려한 순편익 추정결과, 충방전이 가능한 가상발전소 방식의 경우 월평균 운행비용의 67~85% 수준으로 나타났다. 이러한 수요자원 순편익이 소비자에게 효과적으로 분배되는 요금체계가 적용될 경우 시장참여유인이 높을 것으로 추정된다. As variable renewable sources rapidly increase due to the Energy Transition plan, integration cost of renewable sources to the power system is rising sharply. The increase in variable renewable energy reduces the capacity factor of existing traditional power capacity, and this undermines the efficiency of the overall power supply, and demand resources are drawing attention as a solution. In this study, we analyzed how much electric vehicle demand resouces, which has great potential among other demand resources, can reduce power supply costs if it is used as a flexible resource for renewable generation. As a methodology, a stochastic form of power system optimization model that can effectively reflect the volatile characteristics of renewable generation is used to analyze the cost induced by renewable energy and the benefits offered by electric vehicle demand resources. The result shows that virtual power plant-based direct control method has higher benefits than the time-of-use tariff, and the higher the proportion of renewable energy is in the power system, the higher the benefits of electric vehicle demand resources are. The net benefit after considering commission fee for aggregators and battery wear-and-tear costs was estimated as 67% to 85% of monthly average fuel cost under virtual power plant with V2G capability, and this shows that a sufficient incentive for market participation can be offered when a rate system is applied in which these net benefits of demand resources are effectively distributed to consumers.

Optimal Operation of Virtual Power Plant with Considering the Demand Response and Electric Vehicles

Heydari Rana,Nikoukar Javad,Gandomkar Majid 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.5

The needs of human communities for electrical energy is increasing every day, and as a result, the price of fossil fuels is steadily increasing. Considering the trend of advances in renewable energy technologies and the support of governments and energy policymakers to make more use of these clean and inexpensive resources. Limitations such as low capacity, the uncertainty of output power and stability issues have made it costly and diffi cult to use Distributed Energy Resources (DERs). To solve these problems, a new concept known as Virtual Power Plant (VPP) has been proposed to facilitate the exploitation of DERs. The VPP is a set of DERs that are put together for market participation. Also, eff orts to reduce the amount of environmental pollution have replaced the use of Electric Vehicles (EV) instead of internal combustion engines. Regarding this paper, a new model for optimizing virtual power plant is presented. In this model, the Demand response (DR) has been used, whose modeling is based on Price-Based Demand Response for ordinary loads and incentive. To solve the problem a mixed integer linear programming model is proposed to maximize the profi t of the virtual power plant. In order to see the eff ectiveness and satisfying performance of proposed model, a case study including DERs, EV, and loads is studied as test system. The simulation results using Matlab and GAMS show the effi ciency of the proposed model and proves that simultaneous use of the price-based demand response program, smart charging, and the participation of electric vehicles in demand responses reduces operating costs

Local-Generator-Based Virtual Power Plant Operation Algorithm Considering Operation Time

Park, Sung-Won,Park, Yong-Gi,Son, Sung-Yong The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.12 No.6

A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.

Local-Generator-Based Virtual Power Plant Operation Algorithm Considering Operation Time

Sung-Won Park,Yong-Gi Park,Sung-Yong Son 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.6

A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.

Local-Generator-Based Virtual Power Plant Operation Algorithm Considering Operation Time

박성원,박용기,손성용 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.6

A virtual power plant (VPP) is a system that virtually integrates power resources based on the VPP participating customer (VPC) unit and operates as a power plant. When VPP operators manage resources to maximize their benefits, load reduction instructions may focus on more responsive VPCs, or those producing high profitability, by using VPC resources with high operation efficiency. VPCs may thus encounter imbalance problems during operation. This imbalance in operation time would bring more participation for some VPCs, causing potential degradation of their resources. Such an operation strategy would be not preferable for VPP operators in managing the relationship with VPCs. This issue impedes both continual VPC participation and economical and reliable VPP operation in the long term. An operation algorithm is therefore proposed that considers the operation time of VPC generators for mandatory reduction of power resource consumption. The algorithm is based on constraints of daily and annual operation times when VPP operators of local generators perform capacity-market power transactions. The algorithm maximizes the operator benefit through VPP operations. The algorithm implements a penalty parameter for imbalances in operation times spent by VPC generators in fulfilling their obligations. An evaluation was conducted on VPP operational effects by applying the algorithm to the Korean power market.

Time-Series Estimation based AI Algorithm for Energy Management in a Virtual Power Plant System

Yeonwoo LEE(Yeonwoo LEE) 한국인공지능학회 2024 인공지능연구 (KJAI) Vol.12 No.1

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.