# Top PDF Time-Varying Optimization and Its Application to Power System Operation

### Time-Varying Optimization and Its Application to Power System Operation

The first-order algorithm we propose is the regularized proximal primal-dual gradi- ent algorithm, and we develop a comprehensive theory on its tracking performance. Specifically, we provide analytical results in terms of tracking a KKT point, and derive bounds for the tracking error defined as the distance between the algorithmic iterates and a KKT trajectory. We then provide sufficient conditions under which there exists a set of algorithmic parameters that guarantee that the tracking error bound holds. Qualitatively, the sufficient conditions for the existence of feasible parameters suggest that the problem should be “sufficiently convex” around a KKT trajectory to overcome the nonlinearity of the nonconvex constraints. The study of feasible algorithmic parameters motivates us to analyze the continuous-time limit of the discrete-time algorithm, which we formulate as a system of differential inclu- sions; results on its tracking performance as well as feasible and optimal algorithmic parameters are also derived. Finally, we derive conditions under which the KKT points for a given time instant will always be isolated so that bifurcations or merging of KKT trajectories do not happen.

### Study of Kalman Filtering Techniques and Its Application for Optimal Power System Operation

KEYWORDS: Distributed generation, grid connection, Kalman filter algorithm, load-concentration-bus, optimal location, optimal size, power loss I.INTRODUCTION IN response to the recently improved prices of oil and natural gas, it is expected that the electrical energy industry will go through significant and fast change with regard to its framework, function, preparing, and control. Moreover, because of new restrictions placed by cost-effective, governmental, and ecological factors, styles in power system preparing and function are being forced toward maximum usage of current power facilities with limited working edges[2]. Therefore, the electrical powered power companies are attempting to achieve this purpose via many different ways, one of which is to delay the distribution generation (DG) remedy by a separate energy manufacturer (IPP) to meet growing customer fill demand. In this case, deferral attributes obtained by the IPP rely on the step-by-step system stability enhancement made by the DG remedy[1]-[4]. The DG is based on the alternative energy such as energy cell, photovoltaic or PV and wind energy as well as mixed heat and energy gas generator, micro-turbine, etc. Now, it becomes an essential important component of the modern energy system recently for several reasons.

### Dynamic Optimization of a Subcritical Steam Power Plant under Time-Varying Power Load

* Correspondence: george.bollas@uconn.edu; Tel.: +1-860-486-6037 Abstract: The increasing variability in power plant load, in response to a wildly uncertain electricity market and the need to to mitigate CO 2 emissions, lead power plant operators to explore advanced options for efficiency optimization. Model-based, system-scale dynamic simulation and optimization are useful tools in this effort, and the subject of the work presented here. In prior work, a dynamic model validated against steady-state data from a 605 MW subcritical power plant was presented.

### Time Varying Acceleration Coefficients with Dominant Social Component particle swarm optimization for interconnected power system

system that significantly improved the transient response for corresponding load perturbations. C.T.Pan and C.M.Liaw [4] presented an adaptive controller for load frequency control. Aleksandar M.Stankovic et al ., [5] presented a physically motivated augmentation of the standard integral controller in LFC. Janardan Nanda et al ., [6] investigated continuous discrete mode interconnected hydro thermal system using conventional integral and proportional integral controllers (system works in continuous mode, controller works in discrete mode). Seyed Abbas Taher and Reza Hematti [7] presented quantitative feedback theory for load frequency control. I. A. Chidambaram and B. Paramasivam [8] designed a Genetic Algorithm (GA) based controllers with Integral Square Error criterion for the decentralized load frequency control of two area interconnected thermal reheat power systems with and without Redox Flow Batteries (RFB) considering Thyristor Controlled Phase Shifter (TCPS) in the Tie-line. H. A. Shayanfar et al. , [9] described a Multi Input Multi Output (MIMO) design technique based on the Characteristic Loci (CL) method applied to load frequency control of interconnected power system. Wen Tan [10] discussed a unified PID tuning method for load frequency control of interconnected power system. Gayadhar Panda et al ., [11] presented a modified genetic algorithm based optimal selection of integral gain and frequency bias constant for load frequency control of multi area interconnected power system. K. P. Singh Parmar et al. , [12] presented output feedback controller design for two area interconnected power system. Armin Ebrahimi Milani and Babak Mozafari [13] presented new genetic algorithm based method for achieving optimal gains in two area interconnected power system. Serhat Duman and Nuran Yorukeren [14] presented GSA method for determination of optimal PID parameters in two area interconnected power system. Rita Saini et al ., [15] presented Bacterial Foraging Optimization (BFO) method for two area interconnected power system.

### The Optimization and Implementation of Collaborative System for Power Grid Operation Mode Calculation

JILIN CHEN, FENGQUAN ZHANG, ZHONGHUA GUO and WEIJIANG QIU ABSTRACT The collaborative system for power grid operation mode calculation implements data management of multi-level paralleling operated dispatching department’s indifferent places and joint operation mode calculation, which is based on the calculated data of power grid operation modes. The transient stability analysis monitors the components of electrical variation curve through the network transmission to the web page. When more users and more curves reaches a certain extent, the overall simulation time is longer and the curve is stuck because of the limitation of the transmission bandwidth and the refresh rate of the web page. This paper, The Douglas-Peucker algorithm is used in system to solve the data transmission of large amount of data delay problem and achieve the transmission of the large amount of data, the overall simulation time of curve in the web page display is decreased, and the curves are refreshed smoothly.

### Study on Application and Operation Optimization of Hydrocyclone for Solid-liquid Separation in Power Plant

𝑢 𝑡 𝑟 𝑛 = 𝐶 (2) n–Index, 0.5∼0.9, decide by the operation condition. It can be seen that the tangential velocity will increased, the hydrostatic pressure will be into the dynamic pres- sure with the reduced radius of gyration. In other words, the ﬂuid has had a rotating movement. The Serous gran- ules are disjoined two parts, one of it moves to the hy- drocyclone wall in the role of centrifugal force, at the same time, other part moves to the inside of the cyclone chamber by the role of radial velocity ﬂow. Coarse grain attains the higher speed by the centrifugal force. When the velocity is bigger than the radial velocity, the parti- cles transferred towards the wall, fell into the underﬂow region, taken by the underﬂow pipe from Chamber for the coarse-grained product. When the velocity is smaller than the radial velocity, the particles transferred to the inside of the chamber, entered into the overﬂow region, taken by the overﬂow tube from Chamber for the ﬁne product. And when the velocity is equal to the radial velocity, the particle will be swing at the radial of r. If the ﬂow region r on the decline, they will ﬂow into the underﬂow area, otherwise they will enter into the over- ﬂow. If the axial velocity is amount to zero, one half of the gypsum slurry will be into the overﬂow, and another will enter the Chamber. The size of particle is separa- tion grading, which is the basic principles of hydrocyclone classiﬁcation.

### Optimization of Solar Power by varying Tilt Angle/Slope

However, theoretical as well as experimental results have shown that this simplifying assumption is generally far from reality [4]. Thus, it appears that sky radiance should be treated as anisotropic, particularly because of the strong forward scattering effect of aerosols [5–8]. Reviews on transforming data recorded by horizontal pyranometers to data that would have been received by tilted surfaces are given by many researches [9–14]. The best way to collect maximum daily energy is to use tracking systems. A tracker is a mechanical device that follows the direction of the sun on its daily sweep across the sky. The trackers are expensive, need energy for their operation and are not always applicable. Therefore, it is often practicable to orient the solar collector at an optimum tilt angle, and to correct the tilt from time to time. Several interesting articles have been devoted to this problem. Most of these articles treat the problem qualitatively and quantitatively [15–17], while others articles give an analytical treatment [18–21]. It is reported in the literature that in the northern hemisphere, the optimum orientation is south facing and the optimum tilt angle depends only on the latitude. No definite value is given by researchers for the optimum tilt angle. Further review of literature shows that there is a wide range of optimum tilt angle as recommended by different authors, and they are mostly for specific locations.

### Scenario Generation of Wind Farm Power for Real-Time System Operation

This work presents an efficient and scalable method to pro- duce scenarios for a large system of wind farms. This method utilizes probabilistic forecasts using a conditional heteroscedas- tic model, and spatio-temporal dependencies are captured using a Gaussian copula. The literature on scenario generation is largely focused on the day-ahead time horizon, whereas this work considers the real-time applications. Although there is much overlap between the two problems, there are major dif- ferences that arise from the change in time scale. Most notably, real-time applications operate under much tighter time con- straints. Consider that the MISO LAC tool executes every 15 minutes, and the UC optimization problem must be solved within 5 minutes. The scenarios that correspond to the present

### Stochastic optimization of offshore wind power plants operation for maximizing energy generation: focusing on the electric power system optimization and cost minimization

System reliability assessment is maybe the most interesting improvement to be taken into account for future versions of this optimization model. This assesses the possibility of having redundancy for system components subject to failure. For the implementations of these improvements a more complex programming is necessary. It means the removal of some of the current constrains, additions of new formulation and variables, sets, number of scenarios, etc. to the detriment of the execution time which has to be checked along with the main programming after all this changes in order to analyzed if the optimization model is feasible or not. This point is very important because the optimization time in the solver increases exponentially and in the present project, when it was tried to consider ring layout, it was no possible to obtain any result because the running time was huge.

### Modified particle swarm optimization for economic emission load dispatch of power system operation

3 Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia Received: 25.07.2013 • Accepted/Published Online: 30.09.2013 • Printed: 31.12.2015 Abstract: This paper proposes a modified particle swarm optimization considering time-varying acceleration coeﬃcients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO) algorithm. The idea is to enhance the performance and robustness of classical PSO. The price penalty factor method is used to transform the multiobjective EELD problem into a single-objective problem. Then the weighted sum method is applied for finding the Pareto front solution. The best compromise solution for this problem is determined based on the fuzzy ranking approach. The IEEE 30-bus system has been used to validate the eﬀectiveness of the proposed algorithm.

### Probabilistic reliability management approach and criteria for power system real-time operation

a.) We employ the DC power flow approximation [3] to express all network constraints. b.) We model an “acceptable system trajectory”, denoted as (x 0 , x c , x b c ) ∈ X a in (7), as the exis- tence of a steady-state equilibrium with no loss of load throughout: (i) the pre-contingency operation, (ii) the short-term interval after the occurrence of any contingency c ∈ C c and before the application of the respective corrective control actions, and, (iii) the final state reached by following the application of corrective control actions while taking into account their possible failures. It follows that any case under which the mathematical constraints expressing the system operational limits would be violated for at least one of these three regimes is regarded in our implementation as an “unaccaptable system trajectory”.

### Application of Genetic Algorithm in Power System Optimization with Multi-type FACTS

The deregulated market model is progressively taking place in power industries all over the world. With such liberalization, a third-party access is provided by separating the generation & transmission of power, and the consumers are empowered to pick from the private utilities as per their own choices for the electricity-buying purpose. However, in order to grab a larger customer-base and survive in the market, these suppliers might cause the commercial rivalry to take an unhealthy turn and resort to the unplanned power exchange through transmission lines. Parallel to restructuring of market, the industry also faces the challenge of satisfying the ever-increasing growth of load demand. All these force to operate some of the transmission lines close to their thermal limits which could result in being overstressed and eventually in congestion. On the other hand, the up gradation of power network by building new infrastructures like transmission lines, substations etc, most of the time, turns out to be not practical due to political, economical & environmental constraints.

### On the Absence of Spurious Local Trajectories in Time-varying Nonconvex Optimization

In this paper, we study the landscape of an online nonconvex optimization problem, for which the input data vary over time and the solution is a trajectory rather than a single point. To understand the complexity of finding a global solution of this problem, we introduce the notion of spurious (i.e., non-global) local trajectory as a generalization to the notion of spurious local solution in nonconvex (time-invariant) optimization. We develop an ordinary differential equation (ODE) associated with a time-varying nonlinear dynamical system which, at limit, characterizes the spurious local solutions of the time-varying optimization problem. We prove that the absence of spurious local trajectory is closely related to the transient behavior of the developed system. In particular, we show that if the problem is time-varying, the data variation may force all of the ODE trajectories initialized at arbitrary local minima at the initial time to gradually converge to the global solution trajectory. We study the Jacobian of the dynamical system along a local minimum trajectory and show how its eigenvalues are manipulated by the natural data variation in the problem, which may consequently trigger escaping poor local minima over time.

### A hybrid optimization problem at characteristic times and its application in agroecological system

The generalized model of these problems is a hybrid optimization problem involving state delay with characteristic time and parameter control. In this paper, we ﬁrst present a general question on state delays, then design optimization algorithms. Finally, two ex- amples in the ﬁeld of pest control are given to exhibit the eﬀectiveness of the proposed optimization algorithm.

### The Impact of setting business intelligence System on the power of achieving useful information and its Operation

With regard to the wide spectrum of Administration of health turnover, in order to have control and surveillance on the Services and costs of treatment, the BI center has been settled in year 1390 to achieve high quality information, precise decisions and exact data. It will improve the system operation and prevent time wasting. With respect to the issues that have been mentioned and after working more than three years with this system, the following questions will be posed:

### A New Particle Swarm Optimization Algorithm to Hierarchy Multi-objective Optimization Problems and Its Application in Optimal Operation of Hydropower Stations

Index Terms—multi-objective optimization, particle swarm optimization algorithm, daily generation scheduling I. I NTRODUCTION The hydropower stations are important economic and kinetic energy unit in power system, which, on the one hand, can gain capacity benefits through peak load regulation, frequency modulation and undertaking spinning reserve capacity; and, on the other hand, can gain electricity quantity benefit by replacing the thermal power stations [1]. The traditional economic benefits of hydropower systems generally only consider the generation benefit, and rarely include dynamic benefits, such as peak-energy capacity benefits, spinning reserve capacity benefits, etc [2], which is disadvantageous to optimize energy structure and resource allocation, and economically dispatch and safety operate of grid. With the development of power market in our country, the capacity benefits of hydropower system have played a more and more important role. It's an important issue worthy of deep study to change the optimal scheduling model which includes capacity and electricity quantity benefits from the traditional scheduling model which

### A new recursive algorithm for time-varying autoregressive (TVAR) model estimation and its application to speech analysis

B. Simulation Results with Real Speech A similar simulation is carried out by using a speech segment “tea” from [13] with a length of 0.1 second, which is shown in the top left panel of Fig. 2. It was downsampled to 2 kHz in order to focus on low frequency formants. A 12-order model is applied to both algorithms and power series with q=4 is used for TVLP. Other settings are identical to that in the previous example, except λ e = 0.9 are used to track fast power changing in real data and the regularization parameter needs to be multiplied with a constant factor around 5 to reflect the increase in noise power. Results are presented in Fig. 2. The spectrogram only shows the first and second tracts. The estimated tracts of the proposed algorithm agree well with the real one while the conventional TVLP algorithm suffers from slow tracking and significant deviation. As for the pole trajectories, the TVLP have many poles near or even outside the unit circle, which may cause instability.

### Review Of Self-Tuning Controller And Its Application In Electrical Power System

Index Terms: Adaptive cotroller, Self-tuning controller, dynamic performance, power system, Kalman filtering. ———————————————————— 1 I NTRODUCTION SELF-TUNING controller was originally proposed by Kalman in 1958. However, because of the unavailability of high-speed computers and inadequately developed theory, this technique was not taken up seriously at that time. The breakthrough came with the work reported by Astrom and Wittenmark in 1973. Since then this technique has become popular, especially due to the advent of microprocessors, which make it feasible to implement the STC algorithms [1]. Self-tuning controller (STC) is one of the techniques of adaptive control.