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.

Hardware and Control Implementation of Electric Springs for Stabilizing Future Smart Grid With Intermittent Renewable Energy Sources

Abstract: In this paper, the details of practical circuit and control implementation of an electric spring for reactive power compensation and voltage regulation of the ac mains are presented. With Hooke's law published three centuries ago, power electronics-based reactive power controllers are turned into electric springs (ESs) for regulating the ac mains of a power grid. The proposed ES has inherent advantages of: 1) ensuring dynamic load demand to follow intermittent power generation; and 2) being able to regulate the voltage in the distribution network of the power grid where numerous small-scale intermittent renewable power sources are connected. Therefore, it offers a solution to solve the voltage fluctuation problems for future power grids with substantial penetration of intermittent renewable energy sources without relying on information and communication technology. The proof-of-concept hardware is successfully built and demonstrated in a 10-kVA power system fed by wind energy for improving power system stability. The ES is found to be effective in supporting the mains voltage, despite the fluctuations caused by the intermittent nature of wind power.

Modeling and Analysis of the Role of Energy Storage for Renewable Integration: Power Balancing

Abstract: The high variability of renewable energy is a major obstacle toward its increased penetration. Energy storage can help reduce the power imbalance due to the mismatch between the available renewable power and the load. How much can storage reduce this power imbalance? How much storage is needed to achieve this reduction? This paper presents a simple analytic model that leads to some answers to these questions. Considering the multitimescale grid operation, we formulate the power imbalance problem for each timescale as an infinite horizon stochastic control problem and show that a greedy policy minimizes the average magnitude of the residual power imbalance. Observing from the wind power data that in shorter timescales the power imbalance can be modeled as an iid zero-mean Laplace distributed process, we obtain closed form expressions for the minimum cost and the stationary distribution of the stored power. We show that most of the reduction in the power imbalance can be achieved with relatively small storage capacity. In longer timescales, the correlation in the power imbalance cannot be ignored. As such, we relax the iid assumption to a weakly dependent stationary process and quantify the limit on the minimum cost for arbitrarily large storage capacity.

Genetic Algorithm Based Demand Side Management for Smart Grid

Abstract: Electricity usage at electricity rush hour (peak hour) may vary from each and every service area such as industrial area, commercial area and residential area. Equalizing the power consumption in industry may lead to the utilization of power in other service areas in an efficient way. Although industries have comparably lesser number of power consuming device types than other service areas the power consumption is quite high. To meet the demands rising in the industry, shiftable loads (devices) can be redistributed equally to all the working time slots based on the average power utilization. It can be done in a flexible manner by shaping the loads using Demand Side Management (DSM) technique in Smart Grid. The main objective is to minimize the power utilization during the electricity rush hour by effectively distributing the power available during off-peak hour. Evolutionary algorithm can be well adapted to problems where optimization is the core criteria. Any maximization or minimization problem can be solved efficiently using evolutionary algorithm. Hence, to obtain the optimized fitness function of load redistribution in industry Genetic Algorithm in Demand Side Management (GA-DSM) is chosen and it has benefited with an overall reduction of 21.91% which is very remarkable. In addition to this the evaluation of the fitness function using GA-DSM is carried out in other two industrial dataset models (steel plant and wind power plant) which is unavailable so far in the literature.

Corrective Voltage Control Scheme Considering Demand Response and Stochastic Wind Power

Abstract: This paper proposes a new approach for corrective voltage control (CVC) of power systems in presence of uncertain wind power generation and demand values. The CVC framework deals with the condition that a power system encounters voltage instability as a result of severe contingencies. The uncertainty of wind power generation and demand values is handled using a scenario-based modeling approach. One of the features of the proposed methodology is to consider participation of demand-side resources as an effective control facility that reduces control costs. Active and reactive redispatch of generating units and involuntary load curtailment are employed along with the voluntary demand-side participation (demand response) as control facilities in the proposed CVC approach. The CVC is formulated as a multi-objective optimization problem. The objectives are ensuring a desired loading margin while minimizing the corresponding control cost. This problem is solved using e-constraint method, and fuzzy satisfying approach is employed to select the best solution from the Pareto optimal set. The proposed control framework is implemented on the IEEE 118-bus system to demonstrate its applicability and effectiveness.

System operation with a significant wind power penetration

Abstract: With increasing levels of wind generation capacity on electricity systems, system operators will need to adapt their system operation policy to facilitate the efficient and cost effective integration of wind power. This paper illustrate the relative merits of adopting different system operational approaches on a system with significant wind power capacity. The impact on conventional generation, reserve levels and emissions are assessed and the implications are discussed. The illustrations show that an operational approach, which incorporates wind forecast information, while considering an increased need for reserve due to wind power, results in a more efficient integration of the wind capacity.