Spacial coordination between data centers and power system considering uncertainties of both source and load sides

The expansion of low‐carbon power generation has led to increased complexity in the dispatching mode of the power system. To achieve low‐carbon economic operation for multi‐regional power systems, this study proposes a decentralized dispatch architecture and a bi‐level low‐carbon economic dispatching (LCED) model. At the upper level, the model proposes a carbon emission constraint mechanism that is tailored to the coordinated operation of multiple regions, aiming to minimize the total operating cost. At the lower level, the model considers the reduction of carbon emission obligation on the load side and introduces the carbon emission flow (CEF) theory to calculate the degree of reduction in carbon emission intensity. To accommodate the decentralized autonomy and information privacy of different regions, a distributed alternating direction method of multipliers (D‐ADMM) algorithm is adopted to solve the upper‐level problem for the multi‐regional power system, enabling the fully distributed solution of the bi‐level optimization problem. Finally, the effectiveness of the proposed bi‐level model is validated through a case study on the modified IEEE 39‐bus system, which demonstrates that the model can significantly reduce carbon emissions and improve the level of renewable power consumption.

The integration of large shares of wind generation in power systems requires the development of new algorithms and forecasting tools for making decisions in the operational domain taking into account wind generation forecast uncertainties. One of these decisions regards operating reserve requirements to meet load and wind variations. The aim of this paper is therefore to address this issue from a risk evaluation perspective, showing that it is possible to describe the consequences of each possible reserve level through a set of risk indices useful for decision-making. The new reserve management tool described in this paper is intended to support the transmission system operator (TSO) in defining on-line the operating reserve needs for the daily and intraday markets. Decision strategies like setting an acceptable risk level or finding a compromise between economic issues and the risk of loss of load are explored. A case-study based on the Portuguese power system demonstrates the usefulness and efficiency of the tool.

The trend of low-carbon power puts forward new standards and challenges for the operation of power system, and also makes the optimal dispatching of power system more difficult. In order to better realize the low-carbon economic operation of the power system, this paper proposes a bi-level low-carbon economic dispatching (LCED) model for multi-regional power system. In the upper level, a carbon emission constraint based on event-driven mechanism tailored for coordinated operation of multiple regions is proposed, and the optimal objective is to minimize the total operating cost of the system. In the lower level, the reduction of carbon emission obligation on the load side is considered, and the optimal objective is to maximize the low-carbon utility on the load side. Thus, the synergy of the low-carbon goal on both source and load sides is achieved. Finally, through the simulation of the modified IEEE 39-bus system, it is verified that the proposed bi-level model can effectively reduce operating costs and reduce carbon emissions, and improve the level of renewable energy consumption.

Like conventional power plants, wind power plants must provide the power quality required to ensure the stability & reliability of the power system. Increasing amount of wind turbine are connected to electrical power system in order to mitigate the negative environmental consequence of conventional electricity generation. While connecting wind turbine to grid it is important to understand source of disturbance that affect the power quality. In general voltage & frequency must be kept as stable as possible. This stability can be obtained by using FACTS devices. Recently voltage-source or current-source inverter based various FACTS devices have been used for flexible power flow control, secure loading and damping of power system oscillation. Some of those are used also to improve transient & dynamic stability of wind power generation system (WPGS). In this paper, we propose the static reactive compensator (STATCOM) based on voltage source converter (VSC) PWM technique to stabilize grid connected squirrel cage wind generator system. A simple control strategy of STATCOM is adopted where only measurement of rms voltage at the wind generator terminal is needed, there is no need of reactive power measurement. Fuzzy logic controller is used as the control a methodology of STATCOM, rather than conventional PI controller. The voltage sag and swell improvement of WPGS is compared with both fuzzy and PI controller. Moreover, the steady state capacitor value used with induction generator reduced by certain percentage when STATCOM is used with WPGS.

In view of uncertainties caused by large-scale wind power integration, energy storage system (ESS) is being considered to stabilize the fluctuation of wind power. In this paper, the influence of ESS on power system operation with wind power is analyzed in detail, and an economic dispatch (ED) model with wind power and ESS is proposed based on scenario set. First, the initial scenario set of wind power output is generated by the Monte Carlo sampling. To overcome the shortcoming of heavy dependence on the initial clustering centers, which usually leads to unstable clustering results, the k-means clustering is improved by combining self-organizing feature map neural network and particle swarm optimization (PSO). Then, the initial scenario set is reduced based on this improved k-means clustering method. Finally, an ED model solved by PSO is used to minimize the comprehensive power generation cost based on the reduced scenario set. Taking IEEE-39 bus system as an example, the scenario-set-based ED model is implemented in this paper. The simulation results show that, when solving the ED problem with wind power and ESS, the proposed method considering scenario reduction makes not only the clustering index better, but also the results of ED more reasonable.

Optimization dispatch with flexible load participation in new power systems significantly enhances renewable energy accommodation, though the potential of flexible loads remains underexploited. To improve renewable utilization efficiency, promote wind/PV consumption and reduce carbon emissions, this paper establishes a low-carbon economic optimization dispatch model for active distribution networks incorporating flexible loads and tiered carbon trading. First, a hybrid SSA (Sparrow Search Algorithm)–CNN-LSTM model is adopted for accurate renewable generation forecasting. Meanwhile, multi-type flexible loads are categorized into shiftable, transferable and reducible loads based on response characteristics, with tiered carbon trading mechanism introduced to achieve low-carbon operation through price incentives that guide load-side participation while avoiding privacy leakage from direct control. Considering the non-convex nonlinear characteristics of the dispatch model, an improved Beluga Whale Optimization (BWO) algorithm is developed. To address the diminished solution diversity and precision in conventional BWO evolution, Tent chaotic mapping is introduced to resolve initial parameter sensitivity. Finally, modified IEEE-33 bus system simulations demonstrate the method’s validity and feasibility.

The electricity supply chain system consists of power plants, transmission and distribution. Differences in power plant characteristics cause differences in fuel costs and emissions. Inaccuracies in scheduling the plant have an impact on the surge in fuel use. This becomes the basis for the optimization of power plant scheduling. Optimization on the generator side is usually using the economic dispatch model. However, the Economic Dispatch Model does not consider optimization on the transmission network. Optimization on the transmission network is needed because there are losses in the transmission network. Losses will be even greater when the distance between the power plant and the customer is getting further away. So if distance can be minimized, fuel costs can be reduced. Minimizing the distance for shipping goods can use the transportation model, but the transportation model cannot be used for electricity distribution. This is because there are differences between goods and electricity. Therefore, this study proposes the Single Echelon Economic Dispatch (SEED) model. This model is a combination of the economic dispatch model and the transportation model. This model is able to do simultaneous optimization between the generator side and the transmission side. The model is applied to the Mahakam system in East Kalimantan, using all PLN’s power plants. Load consists of two types, namely low load and peak load. As a result, in peak load and low load conditions, the P11 power plant produces the biggest losses and emissions. This is because electricity production in P11 has to go through a longer path compared to other plants. The P11 is also a power plant that requires the highest fuel costs

The existing power system cyber security protection system lacks pertinence for new services and has a low degree of automation. It is urgent to propose a security protection framework for the characteristics of new generation of power system business, especially to improve the attack prevention capability of distributed power sources, flexible and adjustable loads, etc., ensuring the stable operation of the power grid. Aiming at the lack of efficient linkage and coordination of existing cyber security protection devices in new generation of power systems, this paper proposes an interacted response technology for security protection devices based on intelligent learning. Our scheme standardizes and correlates the various threat intelligence collected by the security protection equipment, and use the multi-agent deep reinforcement learning method to realize the issuance and optimization of automated strategies in combination with the analysis results. The interacted strategy of safety protection devices is optimized through collaborative heterogeneous reinforcement learning model. And the validity of interacted configuration is verified for correctness, completeness, redundancy and consistency.

A non-linear convex cost model for economic dispatch in microgrids

In this study, a grid-connected hybrid system composed of a solar and wind power generation system is modelled and analyzed in Matlab/Simulink. In addition, the quality of power generated by the hybrid power generation system is improved by using Fuzzy Logic (FL) and Proportional-Integral (PI) controllers. Measurements of the frequency, voltage, power and harmonics of the system and the grid are evaluated. In addition, the voltage and frequency fluctuation times prior to synchronization between the hybrid generation system and the grid are analyzed. The voltage rises that occur on the grid while the system is idling have been checked. After synchronization, the voltage, power, frequency and phase angle values measured at the load and at the grid in the hybrid system were observed individually. According to the measured values obtained as a result of the simulation study, the performance of the hybrid power generation system is analyzed.

DRL based low carbon economic dispatch by considering power transmission safety limitations in internet of energy

This work presents the analysis and performance of connecting two wind power generation systems with the energy storage at the dc side. Energy storage is desirable to be installed to keep constant output from the wind power generation system. The DC connection of two wind power generation system helps to exchange power between the two systems and can suppress the disturbance of the output power to the utility systems longer than the stand alone system. The performance of connecting two wind generation systems with the energy storage at the dc side has been investigated by using the simulation. The wind power generation system is modeled and simulated by MATLAB/Simulink and the effectiveness of the dc connection of two systems is presented. This effect is easily achieved and implemented without any additional control. The controller measures only the common dc side capacitor voltage of the local system. MATLAB/Simulink simulation verifies the better performance in a certain situation.

This paper presents evolutionary technique to seek the optimal location of FACTS devices in a power system. FACTS controllers in the form of SVC type are introduced. This evolutionary technique is genetic algorithms (GAs). Provided optimal locations, FACTS devices can be used to achieve the optimal power flow (OPF) without any constraint violation and thus to increase the utilization of the lowest cost generation in power system. FACTS location should be reasonably chosen according to their contribution to the general objective of power system economic generation and dispatch. The objective cost function, which consists of the investment costs for this type of FACTS devices and the generation costs, is minimized. Numerical examples will be indicated to obtain the optimal allocation of SVC.

Nowadays voltage instability is a major concern for the secure operation of the electrical power systems. Understanding the effects of wind generators on power system dynamics and stability is crucial given the increasing levels of wind power generation in power systems around the world. This paper shows the dynamic voltage stability analysis with and without renewable energy resource under various operating conditions. The Kundur-10 bus system is being used for the purpose of analysis in the paper. The results show that with different load levels the voltage drops initially and then restores to reference value after the on-load tap changer actives. It has been shown with inclusion of DFIG wind generator improves the voltage profile. The voltage instability effects have been observed by considering different load levels and line outages.

International Journal of Computational Engineering ScienceVol. 05, No. 01, pp. 81-89 (2004) No AccessEVOLUTIONARY PROGRAMMING BASED ECONOMIC DISPATCH WITH LINE FLOW CONSTRAINTSP. SOMASUNDARAM, K. KUPPUSAMY, and R. P. KUMUDINI DEVIP. SOMASUNDARAMSchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author , K. KUPPUSAMYSchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author , and R. P. KUMUDINI DEVISchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author https://doi.org/10.1142/S1465876304002277Cited by:1 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractThis paper presents an efficient, simple and new method for solving Economic Dispatch (ED) problem with line flow constraints through the application of Evolutionary Programming (EP). The controllable system quantities in the base-case state are optimized to minimize some defined objective function subject to the base-case operating constraints. A 10-bus system is taken for investigation. The ED results obtained using EP are compared with those obtained using quadratic programming. The investigations reveal that the proposed algorithm is relatively simple, reliable, efficient and suitable for on-line applications.Keywords:Power System OptimizationEconomic DispatchEvolutionary ProgrammingLine Flow Constraints References B. H. Chowdhury and S. Rahman, IEEE Transaction on power systems 5(4), 1248 (1990). Crossref, Google Scholar Nanda, L. Hari and M. L. Kothari, IEE Proceedings-C 141(1), 1 (1994). Google ScholarJ. Nandaet al., IEE Proceedings-C 139(1), 39 (1992). Google ScholarJ. Y. Fan and L. Zhang, IEEE Transactions on Power Systems 13(2), 320 (1998). Crossref, Google ScholarP. K. Hota, R. Chakrabarti and P. K. Chattopadhyay, Institute of Engineers (India) Journal-EL 81, 21 (2000). Google ScholarJ. Nanda and R. Badri Narayanan, Electrical Power and Energy Systems 24, 723 (2002). Crossref, Google Scholar D. B. Fogel , Evoluationary Computation: Toward a New Philosophy of Machine Intelligence ( IEEE Press , USA , 1995 ) . Google ScholarL. L. Lai and J. T. Ma, IEEE Transactions on Power Systems 12(1), 198 (1997). Crossref, Google ScholarH. T. Yang, P. C. Yang and C. L. Huang, IEEE Transactions on Power Systems 11(1), 112 (1996). Crossref, Google ScholarK. P. Wong and J. Yuryevich, IEEE Transactions on Power Systems 13(2), 301 (1998). Google ScholarT. Jayabarathi, G. Sadasivam and V. Ramachandran, Electric Power Systems Research 52, 261 (1999). Crossref, Google ScholarT. Jayabarathi and G. Sadasivam, European Transaction on Electrical Power 10(3), 167 (2000). Crossref, Google ScholarP. Attaviriyanupapet al., IEEE Transactions on Power Systems 17(2), 411 (2002). Crossref, Google Scholar FiguresReferencesRelatedDetailsCited By 1FDR PSO-based Transient Stability Constrained Optimal Power Flow Solution for Deregulated Power IndustryM. Anitha, S. Subramanian and R. Gnanadass28 Aug 2007 | Electric Power Components and Systems, Vol. 35, No. 11 Recommended Vol. 05, No. 01 Metrics History KeywordsPower System OptimizationEconomic DispatchEvolutionary ProgrammingLine Flow ConstraintsPDF download