Impact of Coal-Electricity Integration on Chinas Power Grid Development Strategy

2013 ◽  
Vol 860-863 ◽  
pp. 2600-2605
Author(s):  
Wei Wang ◽  
Chen Zhang ◽  
Wen Yan Liu
Keyword(s):  
Development Strategy ◽  
Electricity Market ◽  
Industrial Structure ◽  
Power Grid ◽  
Supply And Demand ◽  
Vital Role ◽  
Coal Industry ◽  
Integration Policy ◽  
Demand Structure ◽  
Pool Model

The supply and demand structure of Chinas coal market and electricity market is undergoing profound changes. To respond to the conflict between coal industry and power industry, coal-electricity integration has gained support from The State through relevant policies. The development of coal-electricity integration plays a vital role in balancing the energy industrial structure. This paper introduces the evolution of coal-electricity integration policy and discusses the existing pool model of Chinas coal-electricity integration. And this paper also makes an analysis of coal-electricity integrations impact on the development of power grid, providing recommendations for power enterprises facing the new situation of energy development.

scholarly journals The Impact of Energy Cooperation and the Role of the One Belt and Road Initiative in Revolutionizing the Geopolitics of Energy among Regional Economic Powers: An Analysis of Infrastructure Development and Project Management

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Wu Hao ◽  
Syed Mehmood Ali Shah ◽  
Ahsan Nawaz ◽  
Ali Asad ◽  
Shahid Iqbal ◽  
...  
Keyword(s):  
Development Strategy ◽  
Eastern Mediterranean ◽  
Supply And Demand ◽  
Vital Role ◽  
The Arctic ◽  
Infrastructure Development ◽  
Belt And Road Initiative ◽  
Energy Cooperation ◽  
Belt And Road ◽  
The Impact

This paper examines how the latest mega plan and the Belt and Road Initiative (BRI) will impact the geopolitics of energy and infrastructural development. With a massive change in the supply and demand of global energy and its infrastructure, the transition of international energy order is in the making. While the US is going towards a more isolationist path from its traditional superpower role, there are rising economies such as China, India, Japan, and Russia which are undoubtedly playing a vital role in the geopolitical stage and the other development endeavors. Several regions such as Central Asia, the Arctic, Eastern Mediterranean, and the South China Sea are offering substantial natural gas and oil reserves and drawing global attention to develop energy cooperation. This situation is profoundly influencing the transition of energy order. In this transition, BRI is supposed to play an important role. As a mega development strategy with a robust geostrategic dimension, it purposes to advocate interconnectivity collaboration in framework, exchange, and advancement among the partaking nations. This super arrangement offers a lot of ventures, foundation developments, and modern reconciliation in the energy sector. The country is trying to establish a multilateral platform for endorsing and shielding energy cooperation under BRI. This paper, therefore, attempts to observe how this mega plan will contribute to reshaping the existing energy order as well as the geopolitics of energy with motivation on multifaceted energy collaboration.

scholarly journals Research on Multi-scene and Multi-station Fusion Mode Based on Layered Theory of Energy Internet

2022 ◽  
Vol 2148 (1) ◽  
pp. 012006
Author(s):  
Xiaoliang Yang ◽  
Honggang Zhao ◽  
Hongyuan Ren
Keyword(s):  
Development Strategy ◽  
Energy Flow ◽  
Power Grid ◽  
Supply And Demand ◽  
National Development ◽  
Planning System ◽  
Energy Internet ◽  
The Core ◽  
Flow Convergence ◽  
Fusion Mode

Abstract Multi-station integration is a new form of business in the development of energy Internet and a brand new practice of power iot. It is an innovative form that strengthens the interaction between charge and storage of source network on both sides of energy supply and demand, and enhances the flexibility of power grid by taking substation, energy storage station, distributed energy station and other resources as the core. However, there is not a set of construction mode that can guide implementation, copy and popularize. Therefore, guided by the existing construction practice of multi-station fusion in China and combined with multi-user scenarios, this paper studies the multi-station fusion mode, proposes a multi-station fusion planning system based on EIST theory, gives the fusion mode under different business scenarios, and synchronously constructs a new ecological business chain with multi-station fusion as the core. It aims to make full use of the innate advantages of substation in energy flow convergence, realize the “integration of energy flow, business flow and data flow”, comprehensively support the transformation of digital power grid, and practice the national development strategy of “digital economy” and “digital China”.

Bilateral bidding strategy in joint day-ahead energy and reserve electricity markets considering techno-economic-environmental measures

2021 ◽  
pp. 0958305X2110148
Author(s):  
Mojtaba Shivaie ◽  
Mohammad Kiani-Moghaddam ◽  
Philip D Weinsier
Keyword(s):  
Electricity Market ◽  
Large Scale ◽  
Search Algorithm ◽  
Power Grid ◽  
Mathematical Formulation ◽  
Test System ◽  
Bidding Strategy ◽  
Level Problem ◽  
Optimal Bidding ◽  
Environmental Measures

In this study, a new bilateral equilibrium model was developed for the optimal bidding strategy of both price-taker generation companies (GenCos) and distribution companies (DisCos) that participate in a joint day-ahead energy and reserve electricity market. This model, from a new perspective, simultaneously takes into account such techno-economic-environmental measures as market power, security constraints, and environmental and loss considerations. The mathematical formulation of this new model, therefore, falls into a nonlinear, two-level optimization problem. The upper-level problem maximizes the quadratic profit functions of the GenCos and DisCos under incomplete information and passes the obtained optimal bidding strategies to the lower-level problem that clears a joint day-ahead energy and reserve electricity market. A locational marginal pricing mechanism was also considered for settling the electricity market. To solve this newly developed model, a competent multi-computational-stage, multi-dimensional, multiple-homogeneous enhanced melody search algorithm (MMM-EMSA), referred to as a symphony orchestra search algorithm (SOSA), was employed. Case studies using the IEEE 118-bus test system—a part of the American electrical power grid in the Midwestern U.S.—are provided in this paper in order to illustrate the effectiveness and capability of the model on a large-scale power grid. According to the simulation results, several conclusions can be drawn when comparing the unilateral bidding strategy: the competition among GenCos and DisCos facilitates; the improved performance of the electricity market; mitigation of the polluting atmospheric emission levels; and, the increase in total profits of the GenCos and DisCos.

Energy Management System for Hybrid Microgrids

2021 ◽  
Vol 69 (2) ◽  
pp. 21-30
Author(s):  
Nasreddine ATTOU ◽  
Sid-Ahmed ZIDI ◽  
Mohamed KHATIR ◽  
Samir HADJERI
Keyword(s):  
Energy Management ◽  
Electricity Market ◽  
Management System ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Energy Sources ◽  
Variable Load ◽  
Energy Management System ◽  
Price Variation

Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

scholarly journals Short-Term Forecasting of Electricity Supply and Demand by Using the Wavelet-PSO-NNs-SO Technique for Searching in Big Data of Iran’s Electricity Market

Data ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 43 ◽  
Author(s):  
Mesbaholdin Salami ◽  
Farzad Movahedi Sobhani ◽  
Mohammad Ghazizadeh
Keyword(s):  
Neural Networks ◽  
Electricity Market ◽  
Simulation Optimization ◽  
Supply And Demand ◽  
Electricity Supply ◽  
Wavelet Neural Networks ◽  
Short Term ◽  
Swarm Optimization ◽  
Forecasting Accuracy ◽  
Short Term Forecasting

The databases of Iran’s electricity market have been storing large sizes of data. Retail buyers and retailers will operate in Iran’s electricity market in the foreseeable future when smart grids are implemented thoroughly across Iran. As a result, there will be very much larger data of the electricity market in the future than ever before. If certain methods are devised to perform quick search in such large sizes of stored data, it will be possible to improve the forecasting accuracy of important variables in Iran’s electricity market. In this paper, available methods were employed to develop a new technique of Wavelet-Neural Networks-Particle Swarm Optimization-Simulation-Optimization (WT-NNPSO-SO) with the purpose of searching in Big Data stored in the electricity market and improving the accuracy of short-term forecasting of electricity supply and demand. The electricity market data exploration approach was based on the simulation-optimization algorithms. It was combined with the Wavelet-Neural Networks-Particle Swarm Optimization (Wavelet-NNPSO) method to improve the forecasting accuracy with the assumption Length of Training Data (LOTD) increased. In comparison with previous techniques, the runtime of the proposed technique was improved in larger sizes of data due to the use of metaheuristic algorithms. The findings were dealt with in the Results section.

scholarly journals CHINA’S INDUSTRIAL STRUCTURE UPGRADE IN THE “NEW NORMAL”: EMPIRICAL TEST AND DETERMINANTS

2018 ◽  
Vol 63 (04) ◽  
pp. 1037-1058 ◽  
Author(s):  
WEN XIAO ◽  
JIA-DONG PAN ◽  
LI-YUN LIU
Keyword(s):  
Development Strategy ◽  
Industrial Structure ◽  
Empirical Test ◽  
Supply Side ◽  
New Normal ◽  
Dummy Variable ◽  
Technology Improvement ◽  
Policy Suggestions ◽  
Regional Economy Development ◽  
Supply Side Factors

This paper measures the index of industrial structure upgrade nationally, regionally and provincially by employing angle cosine method. The results show that China’s industrial structure has upgraded and the East is higher than the Northeast and the Midwest. The paper presents an empirical study to examine the effect of variables including demand-side factors, New Normal as a dummy variable and supply-side factors on industrial structure upgrading. It implies that New Normal is not significant, while consumption, investment, technology improvement and labor supply significantly facilitate the upgrade. It highlights policy suggestions designed to adopt innovation-driven strategy and regional economy development strategy.

scholarly journals Non-smooth analysis in a national electricity market model: a complex approach

Memorias ◽  
2018 ◽  
pp. 58-66
Author(s):  
Johnny Valencia ◽  
Gerard Olivar ◽  
Johan Manuel Redondo ◽  
Danny Ibarra Vega ◽  
Carlos Peña Rincón
Keyword(s):  
System Dynamics ◽  
Electricity Market ◽  
Equilibrium Points ◽  
Supply And Demand ◽  
Market Model ◽  
National Network ◽  
Demand Growth ◽  
Zero Rate ◽  
National Electricity Market ◽  
Business Approach

In this paper, we show the preliminary results in a proposed a model for the supply and demand of electricity in a domestic market based on system dynamics. Additionally, the model indicates piecewise smooth differential equations arising from the diagram of flows and levels, using dynamical systems theory for the study of the stability of the equilibrium points that have such a system. A bifurcation analysis approach is proposed to define and understand the complex behavior. Until now, no work has been reported related to this topic using bifurcations criteria. The growing interest in personal ways of self-generation using renewable sources can lead the national grid to a standstill and low investment in the system. However, it is essential to preserve the national network as a power supply support to domestic and enterprise demand. To understand this scenario, we include an analysis of zero-rate demand growth. Under this hypothesis, a none smooth bifurcation appears related to a policy which involves the variation of the capacity charge. As a first significant result, we found that it is possible to preserve the investments in the market since, through the capacity charge parameter, the system dynamics can be controlled. Then, from a business approach, it is necessary to know the effects of the capacity charge as the strategic policy in the system generation price scheme.

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