Optimal Combination Control Technology of Demand Side Resources of Distributed Renewable Energy Power Generation

The paper proposes a new unit commitment model that can promote carbon emission reduction in distributed renewable energy power systems. The model first comprehensively considers the optimal combination of low-carbon demand-side resources such as supply-side resources and demand response, electric vehicles, and distributed renewable energy power generation. Secondly, the model unit scheduling rules fully consider the carbon emission target and the economic target and propose a fuzzy dual-objective optimization method that can consider the relative priority of the target. When solving the optimization model, we improved the particle swarm optimization algorithm. We introduced the “cross” and “mutation” operators in the genetic algorithm to improve the particle swarm algorithm’s global optimization capability. The paper verifies the effectiveness of the model and algorithm through the analysis of a ten computer system.

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Capacity Benefit Margin Evaluation in Multi-area Power Systems Including Wind Power Generation Using Particle Swarm Optimization

Green Energy and Technology - Wind Power Systems ◽

10.1007/978-3-642-13250-6_4 ◽

2010 ◽

pp. 105-123 ◽

Cited By ~ 2

Author(s):

Maryam Ramezani ◽

Hamid Falaghi ◽

Chanan Singh

Keyword(s):

Power Generation ◽

Particle Swarm Optimization ◽

Power Systems ◽

Wind Power ◽

Particle Swarm ◽

Wind Power Generation ◽

Swarm Optimization

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Assessing Renewable Energy Sources for Electricity (RES-E) Potential using a CAPM-Analogous Multi-Stage Model

Energies ◽

10.3390/en12193599 ◽

2019 ◽

Vol 12 (19) ◽

pp. 3599 ◽

Cited By ~ 1

Author(s):

Martinez-Fernandez ◽

deLlano-Paz ◽

Calvo-Silvosa ◽

Soares

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Carbon Capture ◽

Renewable Energy Sources ◽

Carbon Capture And Storage ◽

Offshore Wind ◽

Energy Sources ◽

Low Carbon ◽

Multi Stage ◽

The Cost

Carbon mitigation is a major aim of the power-generation regulation. Renewable energy sources for electricity are essential to design a future low-carbon mix. In this work, financial Modern Portfolio Theory (MPT) is implemented to optimize the power-generation technologies portfolio. We include technological and environmental restrictions in the model. The optimization is carried out in two stages. Firstly, we minimize the cost and risk of the generation portfolio, and afterwards, we minimize its emission factor and risk. By combining these two results, we are able to draw an area which can be considered analogous to the Capital Market Line (CML) used by the Capital Asset Pricing model (CAPM). This area delimits the set of long-term power-generation portfolios that can be selected to achieve a progressive decarbonisation of the mix. This work confirms the relevant role of small hydro, offshore wind, and large hydro as preferential technologies in efficient portfolios. It is necessary to include all available renewable technologies in order to reduce the cost and the risk of the portfolio, benefiting from the diversification effect. Additionally, carbon capture and storage technologies must be available and deployed if fossil fuel technologies remain in the portfolio in a low-carbon approach.

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Integration Capability Evaluation of Wind and Photovoltaic Generation in Power Systems Based on Temporal and Spatial Correlations

Energies ◽

10.3390/en12010171 ◽

2019 ◽

Vol 12 (1) ◽

pp. 171 ◽

Cited By ~ 1

Author(s):

Hua Zhou ◽

Huahua Wu ◽

Chengjin Ye ◽

Shijie Xiao ◽

Jun Zhang ◽

...

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Power Systems ◽

Wind Power ◽

Energy Generation ◽

Copula Model ◽

Spatial Correlations ◽

Temporal And Spatial ◽

Renewable Energy Generation ◽

Pv Power Generation

With the rapid growth of renewable energy generation, it has become essential to give a comprehensive evaluation of renewable energy integration capability in power systems to reduce renewable generation curtailment. Existing research has not considered the correlations between wind power and photovoltaic (PV) power. In this paper, temporal and spatial correlations among different renewable generations are utilized to evaluate the integration capability of power systems based on the copula model. Firstly, the temporal and spatial correlation between wind and PV power generation is analyzed. Secondly, the temporal and spatial distribution model of both wind and PV power generation output is formulated based on the copula model. Thirdly, aggregated generation output scenarios of wind and PV power are generated. Fourthly, wind and PV power scenarios are utilized in an optimal power flow calculation model of power systems. Lastly, the integration capacity of wind power and PV power is shown to be able to be evaluated by satisfying the reliability of power system operation. Simulation results of a modified IEEE RTS-24 bus system indicate that the integration capability of renewable energy generation in power systems can be comprehensively evaluated based on the temporal and spatial correlations of renewable energy generation.

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Operation Optimization of Regional Integrated Energy System Considering the Responsibility of Renewable Energy Consumption and Carbon Emission Trading

Electronics ◽

10.3390/electronics10212677 ◽

2021 ◽

Vol 10 (21) ◽

pp. 2677

Author(s):

Feng Li ◽

Shirong Lu ◽

Chunwei Cao ◽

Jiang Feng

Keyword(s):

Renewable Energy ◽

Energy Consumption ◽

Carbon Emission ◽

Emission Trading ◽

Energy System ◽

Low Carbon ◽

Renewable Energy Consumption ◽

Operation Optimization ◽

Integrated Energy System ◽

Carbon Emission Trading

To “bring carbon emissions to a peak by 2030 and to be carbon-neutral by 2060”, the role of renewable energy consumption and carbon emission trading are promoted. As an important energy consumer of regional energy system, it is necessary for integrated energy system to ensure the low-carbon economic operation of the system. Combined with the responsibility of renewable energy consumption, green certificate trading mechanism, carbon emission rights trading, and China Certified Emission Reduction (CCER), a regional integrated energy system operation optimization model was proposed. The model aims to minimize the total cost of the system, which included with electric bus, thermal bus, and cold bus. Setting different scenarios for the given example, the results show that the optimized model could effectively reduce the operating costs of the system. Moreover, the results also provide an effective reference for the system’s economic and low-carbon operation.

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Research on the construction of carbon emission model of power generation industry in Jilin province

MATEC Web of Conferences ◽

10.1051/matecconf/202235502032 ◽

2022 ◽

Vol 355 ◽

pp. 02032

Author(s):

Weiwei Jiang ◽

Zhiyu Song ◽

Zhongyan Wang ◽

Ping Guo

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Wind Power ◽

Field Test ◽

Carbon Emission ◽

Thermal Power ◽

Jilin Province ◽

Emission Model ◽

Forest Reserves ◽

Installed Capacity

Although Jilin Province has abundant forest reserves and has a relatively large carbon neutral advantage compared to other provinces, the installed capacity of thermal power is still relatively high, and the installed capacity of renewable energy such as wind power, photovoltaic and hydropower is insufficient. This paper builds a carbon emission model for the power generation industry in Jilin Province based on the characteristics of the power generation industry in Jilin Province and years of field test experience.

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Wind-Thermal-Nuclear-Storage Combined Time Division Power Dispatch Based on Numerical Characteristics of Net Load

Energies ◽

10.3390/en13020364 ◽

2020 ◽

Vol 13 (2) ◽

pp. 364

Author(s):

Xin Sui ◽

Shengyang Lu ◽

Hai He ◽

Yuting Zhao ◽

Shubo Hu ◽

...

Keyword(s):

Power Generation ◽

Renewable Energy ◽

Power Systems ◽

Operation Time ◽

Power Dispatch ◽

Generating Mode ◽

Pumped Storage ◽

Time Division ◽

Net Load ◽

Division Operation

In order to satisfy the strategic needs of energy sustainable development, renewable energy has developed rapidly and the power systems have been transformed to a new generation of power systems. In the renewable energy power generation technologies, the fastest developing wind power generation are highly intermittent and fluctuating. When high penetration of renewable power connects to the power grid and participates in the system dispatch, there will be more difficulties and challenges in the energy balance control. In this paper, a wind-thermal-nuclear-storage combined time division power dispatch strategy based on numerical characteristics of net load is proposed, where a specific thermal generating mode and an unconventional nuclear generating mode are discussed. In the strategy, the dispatch time division method is introduced in detail and the sample entropy theory is used to calculate the net load complexity. An adaptive thermal generating mode is determined according to the numerical characteristics of the net load. The nuclear generating modes of constant power operation, time division operation, and net load tracking time division operation are compared and analyzed, respectively. Finally, the wind-thermal-nuclear-storage combined time division power dispatch strategy aiming at decreasing the ramping power of thermal generators is achieved, and the increasing of the participation of pumped storage and improving of the continuous and steady operation time of thermal generators are realized. The experiment simulation is developed on an actual provincial power system in the northeast of China. The results verify that the thermal generator ramping power in the case based on SampEn are reduced, and the participation of pumped storage is improved. When both of the thermal generating mode and nuclear generating mode are according to the changing of net loads, the ramping powers of thermal generators are further decreased.

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Demand-Side Management of Smart Distribution Grids Incorporating Renewable Energy Sources

Energies ◽

10.3390/en12010143 ◽

2019 ◽

Vol 12 (1) ◽

pp. 143 ◽

Cited By ~ 5

Author(s):

Gerardo J. Osório ◽

Miadreza Shafie-khah ◽

Mohamed Lotfi ◽

Bernardo J. M. Ferreira-Silva ◽

João P. S. Catalão

Keyword(s):

Renewable Energy ◽

Power Systems ◽

Demand Response ◽

Distribution System ◽

Renewable Energy Sources ◽

Demand Side Management ◽

Pollutant Emissions ◽

Demand Side ◽

Renewable Energy Resources ◽

Distribution Grids

The integration of renewable energy resources (RES) (such as wind and photovoltaic (PV)) on large or small scales, in addition to small generation units, and individual producers, has led to a large variation in energy production, adding uncertainty to power systems (PS) due to the inherent stochasticity of natural resources. The implementation of demand-side management (DSM) in distribution grids (DGs), enabled by intelligent electrical devices and advanced communication infrastructures, ensures safer and more economical operation, giving more flexibility to the intelligent smart grid (SG), and consequently reducing pollutant emissions. Consumers play an active and key role in modern SG as small producers, using RES or through participation in demand response (DR) programs. In this work, the proposed DSM model follows a two-stage stochastic approach to deal with uncertainties associated with RES (wind and PV) together with demand response aggregators (DRA). Three types of DR strategies offered to consumers are compared. Nine test cases are modeled, simulated, and compared in order to analyze the effects of the different DR strategies. The purpose of this work is to minimize DG operating costs from the Distribution System Operator (DSO) point-of-view, through the analysis of different levels of DRA presence, DR strategies, and price variations.

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