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Base load power plant

About: Base load power plant is a research topic. Over the lifetime, 6121 publications have been published within this topic receiving 96788 citations.


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Journal ArticleDOI
TL;DR: In this paper, the authors present a firm-level engineering-economic analysis of a wind/CAES system with a wind farm in central Texas, load in either Dallas or Houston, and a CAES plant whose location is profit-optimized.

159 citations

Journal ArticleDOI
TL;DR: In this article, a review of the benefits and challenges of concentrated solar power plants (CSPs) in the desert regions is presented and suggested solutions are made to address the challenges.
Abstract: Concentrated solar power plants (CSPs) are gaining momentum due to their potential of power generation throughout the day for base load applications in the desert regions with extremely high direct normal irradiance (DNI). Among various types of the CSPs, solar tower power technologies are becoming the front runners especially in the United States and around the world with the possibility to compete with traditional power generation technologies in terms of efficiency and levelized cost of electricity (LCOE). A bibliometric analysis of the publications on the CSP systems and components since 1990 shows a total of 6400+ publications and reveals an exponential growth due to reasons that CSP systems promises a lot of potential as the future large scale power source for varied applications. This review consolidates the benefits and challenges of the CSP technologies particularly in the desert regions. Thorough literature analysis as well as the meteorological data projects the trend that the CSP systems would become a reality in the Middle East and North Africa (MENA), Australia, Southwestern region of the United States, Southwestern part of China and China/Mongolia border with high direct normal irradiance. However, enormous amount of support and capital investments are needed for making these CSP systems realistic as there is not much power grid network in existence. It is evident that there are multiple challenges specifically in water consumption, materials design and development for the optimum heat transfer fluid, thermal energy storage and receiver subsystems in addition to commercial viability and environmental impacts. Each of the challenges is discussed in detail and suggestions are made to address the challenges.

158 citations

Journal ArticleDOI
TL;DR: In this paper, a control strategy to regulate active power for doubly fed induction generator under various operating conditions is presented to make the wind farm operation more like a conventional power plant, and testing results showing the control performance in the simulated conditions validate the feasibility of the operation in power dispatch upon operator's request, and maintain stability under variant wind speed.
Abstract: As installed capacity of wind power retains a significant proportion of generation mix in the electric system, operators have the increasing expectation that wind turbines should function in some ways similar to the conventional plants. In addition to some basic capabilities to regulate reactive power for voltage support, the counterpart in active power control is also the major concern. This paper presents a control strategy to regulate active power for doubly fed induction generator under various operating conditions. Testing results showing the control performance in the simulated conditions validate the feasibility of the operation in power dispatch upon operator's request, and maintain stability under variant wind speed. Additionally, supplemental functions in generation margin assessment, in spinning reserve support, and in governor droop are presented to make the wind farm operation more like a conventional power plant.

155 citations

Journal ArticleDOI
TL;DR: In this article, a model predictive control (MPC) approach is presented to manage in real-time the energy generated by a grid-tied photovoltaic (PV) power plant with energy storage (ES), optimizing its economic revenue.
Abstract: This work presents a model predictive control (MPC) approach to manage in real-time the energy generated by a grid-tied photovoltaic (PV) power plant with energy storage (ES), optimizing its economic revenue. This MPC approach stands out because, when a long enough prediction horizon is used, the saturation of the ES system (ESS) can be advanced by means of a prediction model of the PV panels production. Therefore, the PV+ES power plant can modify its production so as to manage the power deviations with regard to that committed in the daily and intraday electricity markets, with the objective of reducing economic penalties. The initial power commitment is supposed in this work to be given by a higher level energy management operator. By a proper definition of its objective function, the predictive control allows us to economically optimize the PV+ES power plant performance. This control strategy is tested in simulations with actual data measured for different days with varying meteorological conditions. Results provide a good reference on the economic benefits which can be obtained thanks to the MPC introduction.

154 citations

Journal ArticleDOI
TL;DR: This paper's proposed DR model incorporates a fair billing mechanism that is enhanced with an ex post consumer performance tracking scheme implemented in a context of a virtual power plant aggregating load and generation units.
Abstract: In modern power systems and electricity markets, demand response (DR) programs play an important role enabling the mitigation of critical load periods or price-peaking scenarios, thereby improving system reliability. Price fluctuations, in forward or real-time markets, can be an effective price-based DR mechanism for curtailing or shifting load. However, using dynamic pricing to achieve a desired load profile requires both an accurate demand forecast and knowledge of the price elasticity of demand, which is notoriously difficult to estimate. The limited accuracy of these parameter estimates is the main source of uncertainty limiting appropriate DR implementation. In this paper, we present a novel DR scheme that avoids the need to predict the price elasticity of demand or demand forecast, yet still delivers a significant DR. This is done based on the consumers' submissions of candidate load profiles ranked in the preference order. The load aggregator then performs the final selection of individual load profiles subject to the total system cost minimization. Additionally, the proposed DR model incorporates a fair billing mechanism that is enhanced with an ex post consumer performance tracking scheme implemented in a context of a virtual power plant aggregating load and generation units.

154 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202344
202299
202170
202073
201989
2018103