scholarly journals Two-Stage Optimal Scheduling of Large-Scale Renewable Energy System Considering the Uncertainty of Generation and Load

2020 ◽  
Vol 10 (3) ◽  
pp. 971 ◽  
Author(s):  
Xiangyu Kong ◽  
Shuping Quan ◽  
Fangyuan Sun ◽  
Zhengguang Chen ◽  
Xingguo Wang ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Large Scale ◽  
Thermal Power ◽  
Estimation Method ◽  
Point Estimation ◽  
Low Carbon ◽  
System Operation ◽  
Two Stage ◽  
Point Estimation Method

With the development of smart grid and low-carbon electricity, a high proportion of renewable energy is connected to the grid. In addition, the peak-valley difference of system load increases, which makes the traditional grid scheduling method no longer suitable. Therefore, this paper proposes a two-stage low-carbon economic scheduling model considering the characteristics of wind, light, thermal power units, and demand response at different time scales. This model not only concerns the deep peak state of thermal power units under the condition of large-scale renewable energy, but also sets the uncertain models of PDR (Price-based Demand Response) virtual units and IDR (Incentive Demand Response) virtual units. Taking the system operation cost and carbon treatment cost as the target, the improved bat algorithm and 2PM (Two-point Estimation Method) are used to solve the problem. The introduction of climbing costs and low load operating costs can more truly reflect the increased cost of thermal power units. Meanwhile, the source-load interaction can weigh renewable energy limited costs and the increased costs of balancing volatility. The proposed method can be applied to optimal dispatch and safe operation analysis of the power grid with a high proportion of renewable energy. Compared with traditional methods, the total scheduling cost of the system can be reduced, and the rights and obligations of contributors to system operation can be guaranteed to the greatest extent.

scholarly journals The Polish Practice of Probabilistic Approach in Power System Development Planning

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 161
Author(s):  
Maksymilian Przygrodzki ◽  
Paweł Kubek
Keyword(s):  
Power System ◽  
Large Scale ◽  
Probabilistic Approach ◽  
Estimation Method ◽  
Subsequent Development ◽  
Development Planning ◽  
Point Estimation ◽  
International Exchange ◽  
Technical Standards ◽  
Point Estimation Method

Power systems can be analyzed using either a deterministic or a probabilistic approach. The deterministic analysis centers on studying the quantities and indicators that characterize the operating states of the power system under strictly defined conditions. However, the long-term horizon of planning analyses, the changes of marketing mechanisms, the development of renewable electricity sources, the leaving from large-scale generation, the growth of smart technology and the increase in consumer awareness make the development of transmission networks a non-deterministic problem. In this article, we propose a planning procedure that takes the probabilistic elements into account. This procedure was developed to take into account the high variability of power flows caused by the generation of renewable sources and international exchange. Such conditions of the power system operation forced a departure from deterministic planning. The new probabilistic approach uses the existing tools and experience gained during subsequent development projects. As part of the probabilistic approach, simulations were carried out using the Latin Hypercube Sampling and Two Point Estimation Method algorithms. These methods effectively reduce the computation time and, at the same time, give satisfactory results. The verification was carried out on a test grid model developed in accordance with the technical standards used in the Polish Power System. Effects were assessed using a deterministic and probabilistic approach. This analysis confirmed the practical possibility of using the probabilistic approach in planning the development of transmission network in Poland. When using a probabilistic approach to predict power flow, the criteria of technical acceptability for a given development variant and the manner in which the strategy is determined are of particular importance.

scholarly journals Research on Multi-Timescale Coordinated Method for Source-Grid-Load with Uncertain Renewable Energy Considering Demand Response

2021 ◽  
Vol 13 (6) ◽  
pp. 3400
Author(s):  
Jia Ning ◽  
Sipeng Hao ◽  
Aidong Zeng ◽  
Bin Chen ◽  
Yi Tang
Keyword(s):  
Renewable Energy ◽  
Real Time ◽  
Demand Response ◽  
System Operation ◽  
Real Time Scheduling ◽  
High Penetration ◽  
Time Scheduling ◽  
Grid Load ◽  
Grid Side ◽  
Scheduling Models

The high penetration of renewable energy brings great challenges to power system operation and scheduling. In this paper, a multi-timescale coordinated method for source-grid-load is proposed. First, the multi-timescale characteristics of wind forecasting power and demand response (DR) resources are described, and the coordinated framework of source-grid-load is presented under multi-timescale. Next, economic scheduling models of source-grid-load based on multi-timescale DR under network constraints are established in the process of day-ahead scheduling, intraday scheduling, and real-time scheduling. The loads are classified into three types in terms of different timescale. The security constraints of grid side and time-varying DR potential are considered. Three-stage stochastic programming is employed to schedule resources of source side and load side in day-ahead, intraday, and real-time markets. The simulations are performed in a modified Institute of Electrical and Electronics Engineers (IEEE) 24-node system, which shows a notable reduction in total cost of source-grid-load scheduling and an increase in wind accommodation, and their results are proposed and discussed against under merely two timescales, which demonstrates the superiority of the proposed multi-timescale models in terms of cost and demand response quantity reduction.

scholarly journals Allocation of EV Public Charging Station in Renewable based Distribution Network using HHO Considering Uncertainties and Traffic Congestion

2021 ◽  
Author(s):  
Arnab Pal ◽  
Aniruddha Bhattacharya ◽  
Ajoy Kumar Chakraborty
Keyword(s):  
Distribution System ◽  
Traffic Congestion ◽  
Distribution Network ◽  
Estimation Method ◽  
Point Estimation ◽  
Rank Test ◽  
Voltage Profile ◽  
Charging Station ◽  
Soft Computing Techniques ◽  
Point Estimation Method

Abstract Electric vehicle (EV) is the growing vehicular technology for sustainable development to reduce carbon emission and to save fossil fuel. The charging station (CS) is necessary at appropriate locations to facilitate the EV owners to charge their vehicle as well as to keep the distribution system parameters within permissible limits. Besides that, the selection of a charging station is also a significant task for the EV user to reduce battery energy wastage while reaching the EV charging station. This paper presents a realistic solution for the allocation of public fast-charging stations (PFCS) along with solar distributed generation (SDG). A 33 node radial distribution network is superimposed with the corresponding traffic network to allocate PFCSs and SDGs. Two interconnected stages of optimization are used in this work. The first part deals with the optimization of PFCS’s locations and SDG’s locations with sizes, to minimize the energy loss and to improve voltage profile using harris hawk optimization (HHO) and few other soft computing techniques. The second part handles the proper assignment of EVs to the PFCSs with less consumption of the EV’s energy considering the road distances with traffic congestion using linear programming (LP), where the shortest paths are decided by Dijkstra's algorithm. The 2m point estimation method (2m PEM) is employed to handle the uncertainties associated with EVs and SDGs. The robustness of solutions are tested using wilcoxon signed rank test and quade test.

The Analysis and Application of Energy-Internet in the Low-Carbon Community

2010 ◽  
Author(s):  
Hao Liang ◽  
Weiding Long ◽  
Yingqian Song ◽  
Fang Liu
Keyword(s):  
Renewable Energy ◽  
Large Scale ◽  
Energy Use ◽  
Optimal Path ◽  
Energy Generation ◽  
Hot Water ◽  
Low Grade ◽  
Low Carbon ◽  
Urban District ◽  
Energy Internet

The energy-Internet is a new energy supply method based on urban compact and densely populated community in a low-carbon city. The principle is to connect small energy generation stations and combined heat and power system (CHP) based on distributed energy technology and renewable energy into a network in the urban district. In this way, the cooling, heating and electricity could all back each other up. Each building of the community could collect the energy and then put that energy into the energy-internet to supply the heating and power to buildings. The power in the energy-internet could also be used for charging electric vehicles. So the energy use in the urban community would be basically self-sufficient. The energy generation stations in the energy-internet could be solar power, wind power, biomass cogeneration (including refuse power generation), household fuel cell, low-grade heat in rivers, lakes, urban sewage and soil. In this way, large-scale renewable energy and unused energy could be fully used and applied in a compact and dense community. If the energy-internet is suitable designed, the equipment capacity, energy consumption and CO2 emission of the community could be greatly reduced, energy efficiency could be optimized and improved and the heat island effect could also be alleviated. This article explores three major problems of the construction of energy internet and their solutions: namely, the location and layout of the energy station, the environmental economic dispatch model of the energy internet with power dispatching as an example, the optimal path design of hot water pipe network combined with graph theory and genetic algorithms.

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