Operation Planning Of Power Systems Research Articles

Evaporation Rate-Based Water Cycle Algorithm for Short-Term Hydrothermal Scheduling

Hydrothermal scheduling is a vital step in power system operational planning. It deals with the coordinated operation of hydel and thermal machines so that the cost of production of electrical energy is minimum subject to the satisfaction of the constraints. This paper presents the solution of non-convex short-term hydrothermal scheduling due to valve point effects using an improved version of a meta-heuristic method water cycle algorithm called as evaporation rate-based water cycle algorithm (ERWCA). ERWCA is a nature inspired algorithm based on hydrologic cycle of water that how the raindrops form streams and these streams flow to the rivers and sea. The feasibility and effectiveness of ERWCA have been tested on different hydrothermal test systems consisting of four hydel units configured with one thermal, three thermal and ten thermal units involving all the constraints. The results obtained from these simulations have been compared with other methods such as DE, PSO and GA, and they show that the solutions obtained from ERWCA are superior in terms of cost and computational time. Hence, the proposed ERWCA is a remarkable method for solving short-term hydrothermal scheduling problem.

Distributed control of small-scale power systems using noncooperative games

Distributed energy resources (DERs) coordination problems and load shedding in power systems can be modeled as a distributed resource allocation problem with physical constraints. The dynamic resource allocation problem can be approached using nonlinear methods based on population dynamics. This paper presents an optimization model to minimize the load curtailments needed to restore the equilibrium of the operating point when the system is in a fault condition (e.g., loss of generation). A mathematical model of the proposed strategy for the dispatch generation and an optimal load shedding algorithm are shown. The developed methodology minimizes the load cuts depending on the load relevance of each node of the system, and carrying out the power distribution of the generators under the new demand power condition using the replicator dynamics or the local replicator equation. This model can be used for the operation planning of electrical power systems with DERs. In order to illustrate our methodology, some simulations are performed using the IEEE 34 node test feeder in OpenDSS.

Transmission-constrained generation maintenance scheduling considering market-based demand response

Summary Introduction of smart grid has changed different paradigms in power industry. System-wide demand participation in power system operational planning is one of such influenced paradigms. To comply with these influenced paradigms, generation maintenance scheduling (GMS), as one of the operation planning processes, should be modified to adapt to the new changes. This paper proposes a new model to consider demand response (DR) in the GMS problem. The proposed GMS problem is modelled as a mixed integer linear programming problem and solved for the two known test cases, namely IEEE reliability test system and IEEE 118-bus test system. The results show that considering DR leads to more dispersed and uniformed generation unit maintenance schedules and lower overall system operation cost in comparison with the case in which DR is not considered. Copyright © 2016 John Wiley & Sons, Ltd.

Electric and Energy Coupling for Long-Term Operation Considering Transmission Restrictions

The operation planning of the Brazilian power system is a great challenge due to its size of continental dimensions, large seasonal variations, and predominantly hydroelectric nature. Its operation requires careful planning to reconcile conflicting goals such as spill minimization during the rainy season, and minimization of generation deficits during the dry season, i.e., operation risk minimization. The optimization models for hydrothermal systems currently used to operate large systems do not include the electric network when determining the energy goals. This work aims at modeling a hydrothermal dispatch problem by means of genetic algorithms. The electrical constraints are included by an optimal power flow, which is solved monthly over the planning horizon. The fitness function is composed of criteria that look for using the reservoirs as much as possible during the rainy season, thus, minimizing spills and production costs and, at the same time, catering for the load and limits of energy exchange between the subsystems. The methodology was tested using the 33-bus system.

Development and Operational Planning of Power Systems by Comparing Scenarios during Multi-Objective Optimization

Development and Operational Planning of Power Systems by Comparing Scenarios during Multi-Objective Optimization

Flexibility Envelopes for Power System Operational Planning

Modern power systems are undergoing a transitional phase, increasingly incorporating renewable energy sources (RES) to harness their economic and environmental benefits. The main challenge with this transitional phase is the management of the increased variability and uncertainty in the power balance. Legacy operation and planning practices are gradually seen as becoming inadequate or ill-adapted in addressing this challenge. One particular gap in the state of the art, which is of great importance, is estimating the operational flexibility potential of individual power system assets and their aggregation at the system level. System operators need to evaluate and plan ahead flexibility adequacy for their power systems in order to ensure feasible and economical operation under high RES penetration. Likewise, asset owners need to integrate the notion of asset flexibility as part of their investment and operations decisions. To this end, we propose the concept of the flexibility envelope to describe the flexibility potential dynamics of a power system and its individual resources in the operational planning time-frame. We demonstrate that the resulting envelope dynamics can be a starting point for flexibility adequacy planning in systems with highly variable generation.

Application of combined Newton–Raphson method to large load flow models

Load flow is the most used calculations in power system operation planning. Renewable resources have caused that system operator has to do power flow analysis and/or contingency analysis as fast as possible in order to predict next step in power system control. LU Decomposition of Jacobian matrix remains the most computationally expensive task during Newton–Raphson iterative method. Computational time appears to be critical issue when load flow calculation is performed on large power system load flow models. In this case, Jacobian matrix LU decomposition should not be performed in iterations in which convergence rate is not violated but performed in iterations in which convergence rate drop below specified level. In other words, modified Newton–Raphson Method which eliminates the repeated Jacobian matrix LU decomposition and generic Newton–Raphson method are combined depending on convergence rate. The paper presents application of proposed combined Newton–Raphson method which is based on convergence rate control. Comparison of combined, Shamanskii, generic, and modified Newton–Raphson methods is carried out taking into consideration computational time and number of iterations required to achieve convergence of load flow models of various dimensions.

Risk Assessment for Power System Operation Planning With High Wind Power Penetration

Integration of wind power generation (WPG) is increasing rapidly worldwide. The variability and uncertainty of wind energy may lead to significant load-generation imbalances resulting in large frequency deviations, hence increasing system operational risks, especially in small and isolated power systems with low inertia and limited capabilities of providing frequency responses. This raises the need for investigating alternatives to current power system operation planning approaches to cope with the uncertain nature of the intermittent generation. This paper presents a risk assessment approach to analyze power system security for operation planning under high penetration of wind power generation. The proposed approach deals with not only steady-state voltage and overload evaluations, but also frequency response adequacy. For fast identification of operational limit violations in the proposed risk assessment method, we develop an analytical procedure for approximating frequency response and assessing the consequences of limit violations without performing dynamic simulations. As a result, the frequency response adequacy assessment can be run simultaneously with the steady-state voltage and overload evaluations. The proposed risk assessment approach is illustrated via its application to a model of a power system with high wind power penetration.

Risk-based optimal power flow with probabilistic guarantees

Higher penetration of renewable energy sources and market liberalization increase both the need for transmission capacity and the uncertainty in power system operation. New methods for power system operational planning are needed to allow for efficient use of the grid, while maintaining security against disturbances. In this paper, we propose a risk model for risks related to outages, accounting for available remedial measures and the impact of cascading events. The new risk model is used to formulate risk-based constraints for the post-contingency line flows, which are included in an optimal power flow (OPF) formulation. Forecast uncertainty is accounted for by formulating the relevant constraints as a joint chance constraint, and the problem is solved using a sampling-based technique. In a case study of the IEEE 30 bus system, we demonstrate how the proposed risk-based, probabilistic OPF allows us to control the risk level, even in presence of uncertainty. We investigate the trade-off between generation cost and risk level in the system, and show how accounting for uncertainty leads to a more expensive, but more secure dispatch.

Techniques of the Optimization Based in Artificial Intelligence Applied to Hydrothermal Power Systems Operation Planning

The Hydrothermal Power Systems Operation Planning (HPSOP) aims to determine a strategy for each generation plant at each time interval in order to minimize the expected value of operating costs in the planning horizon. This is a challenge for managers of the Energy Sector, because of the stochastic nature of the problem which is coupled in time (dynamic) and in space (interconnected), large, not separable, non-convex and the target function is non-linear. Therefore, the application of classical techniques presents several limitations. In order to overcome those limitations, improvement of traditional methods, or the development of alternative heuristics is a vital step in the operation of HPSOP. This paper presents an application of two of this new heuristics of Artificial Intelligence: Genetic Algorithms and Ant Colony Optimization. Those techniques were applied to a test system with data from Brazilian power plants. The results showed a good performance when compared with traditional optimization techniques already used in HPSOP. It is noteworthy that in the current study, the applications of traditional optimization techniques and Artificial Intelligence have made use of real characteristics of plant operation without the need to simplify the original formulation.

Short-Term Hydrothermal Dispatch With River-Level and Routing Constraints

Recently, there has been a growing need to consider issues related to multiple uses of water-such as navigation, fishing, or recreation-in the operation planning of electrical power systems, specially in predominantly hydro systems. In short-term models, it is of particular importance to consider maximum/minimum values and ramp limits for the stream level of a river. However, in order to properly represent such constraints, it is also necessary to model in detail the river routing, i.e., the water wave propagation along the channels that connect reservoirs in cascade. This paper proposes a linear programming model to represent river stream-level constraints and river-routing effects in the short-term hydrothermal dispatch problem. Results show the high accuracy of the proposed approach to represent maximum hourly and daily river-level variations as well as the impacts of taking into account a detailed representation of river routing in the operation of hydrothermal systems.

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

A detailed MILP optimization model for combined cooling, heat and power system operation planning

A detailed optimization model is presented for planning the short-term operation of combined cooling, heat and power (CCHP) energy systems. The purpose is, given the design of a cogeneration system, to determine an operating schedule that minimizes the total operating and maintenance costs minus the revenue due to the electricity sold to the grid, while taking into account time-varying loads, tariffs and ambient conditions. The model considers the simultaneous use of different prime movers (generating electricity and heat), boilers, compression heat pumps and chillers, and absorption chillers to satisfy given electricity, heat and cooling demands. Heat and cooling load can be stored in storage tanks. Units can have one or two operative variables, highly nonlinear performance curves describing their off-design behavior, and limitations or penalizations affecting their start-up/shut-down operations. To exploit the effectiveness of state-of-the-art Mixed Integer Linear Program (MILP) solvers, the resulting Mixed Integer Nonlinear Programming (MINLP) model is converted into a MILP by appropriate piecewise linear approximation of the nonlinear performance curves. The model, written in the AMPL modeling language, has been tested on several plant test cases. The computational results are discussed in terms of the quality of the solutions, the linearization accuracy and the computational time.

Mid-short-term risk assessment of power systems considering impact of external environment

Ice flashover, lightning flashover and bird damage are the main reasons that cause transmission facility failure. The impact of these environmental factors on the operational risk levels of power systems should be taken into account in power system maintenance scheduling and operation planning. This paper studies the mid-short-term risk assessment methodology considering the impact of the external environment. The relationship model between natural disasters and transmission lines is presented. The conditional outage rate model and the sampling technique are then proposed considering the correlated outage of multiple transmission lines when a disaster happens. The framework of the mid-short-term risk assessment model is outlined. A test case of Jiangxi provincial power grid validates the proposed model. The results show that the model can quantify the impact of disasters on the forced outage rate of transmission component and their outage correlation, and thus effectively revealing the mid-short-term risk of power systems. The model can facilitate a more strategic decision-making on maintenance scheduling and operation planning of power systems.

Importance Sampling Based Intelligent Test Set Generation for Validating Operating Rules Used in Power System Operational Planning

Decision tree based machine learning methods find a great deal of application in power system reliability assessment studies, wherein essential knowledge in the form of operating rules or guidelines are produced that help operators maneuver the system away from insecurity. Independent test sets are generally used to validate these rules, with the motivation of estimating their classification accuracy and error rates, apart from checking their performance against some interesting situations. This paper proposes an importance sampling based method to generate intelligent test set for validating operating rules. The method is applied for testing decision tree rules derived against voltage collapse problems in western regions of the French power system, and is seen to produce test sets at lesser computation that estimates the rule's classification errors with good accuracy. For a given computation, it also provides richer information on critical operating conditions for which the rule is vulnerable, which helps in further improving the rules.

Transmission‐constrained intrahour coordination of wind and pumped‐storage hydro units

This study proposes a coordination methodology for wind and pumped-storage hydro (PS) units in the day-ahead operation planning of power systems. PS units that can store the extra wind energy will improve the dispatchability of variable wind energy for delivering hourly firmed energy to a power grid. With coordination, the PS unit can offset intrahour wind energy imbalances (i.e. deviations from hourly schedules) and minimise wind energy curtailments. The proposed coordination, which is incorporated into the transmission-constrained unit commitment, can be used by a vertically integrated utility or an independent system operator. The concept of intrahour wind energy imbalances and the wind-PS coordination is illustrated using two case studies. The numerical results for the 6-bus and the IEEE 118-bus system include case studies with and without the coordination of PS and wind generation units. The results that include the intrahour variability of real-time wind speed show the applicability of the proposed wind-PS coordination approach to the short-term power system operation.

Offshore Power System Operation Planning Considering Energy Market Schedules

This paper analyzes selected issues concerning operational strategies for multiterminal dc offshore power systems (OPSs). In the first section, the main challenges regarding the operation of such an OPS are discussed, and a proposal is given for a new observer-based management system (OBMS) used for operation coordination using references from the energy market. In the second section, different operational scenarios for the OPS are investigated in order to present the OBMS application. For this purpose, a test system that considers the expected European future wind power development is introduced. Then, using reference power flows from the hourly market, the influence of the OBMS optimization process on the power flows aiming at minimum deviations from the reference energy market signals will be presented. Some exemplary test simulations are performed and recommendations are given.

Security issues for mega penetration of photovoltaic power generation in future electric power systems. A case study of stability for power swing oscillation using the IEEJ WEST 10‐machine model

AbstractMega penetration of photovoltaic power generation (PV) will be introduced in future electric power systems, dealing with environmental problems such as global warming and energy exhaustion. The authors have pointed out that difficulties will arise in meeting the N‐1 security standard if increases in uncertainties cannot be avoided due to PV penetration. Thus, we have proposed a new concept of “robust power system security” together with several conditions to be satisfied in order to guarantee the N‐1 security standard under uncertainties. In this paper, (1) a model of uncertainties due to PV generation is proposed based on robust power system security; a method for proper parameter selection is also provided. Then, (2) the influence on the stability of the PV and load disconnection from the power system is studied through simulation using the model system; (3) the effect of PV fault ride‐through (FRT) on stability is investigated along with dynamic voltage support (DVS). Finally, it is shown that (4) complicated and burdensome tasks will be considerably increased in power system operation planning and real‐time operation under future circumstances by the mega penetration of PV. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 184(3): 1–13, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22391

Electric Vehicle Aggregator/System Operator Coordination for Charging Scheduling and Services Procurement

In response to the need for the decarbonization of the transport sector, it is expected that large fleets of electric vehicles (EVs) will constitute an important share of the electricity demand. This evolution is likely to be accompanied by a parallel evolution of the electricity supply business with the deployment of smart grid technologies. As a consequence, it is expected that demand will feature higher potential for communication and control, which will enable its active participation in the daily operational planning of power systems. In particular, EVs being equipped with a battery can both defer their demand or inject electricity back into the system. However, to achieve volumes that can have an impact on the system, these demands need to be aggregated and operated as an ensemble. This paper proposes the necessary adaptations to include the input of EV aggregation to electricity markets. This permits the scheduling of EV charging and services in coordination with the system operator thus enhancing the power system's efficiency and security while reducing its environmental impact. Results show that the EVs penetration levels that the system would be able to absorb without requiring expansion of the supply side, are significantly increased when coordination over their charging schedule is performed.

Parallel computing applied to the stochastic dynamic programming for long term operation planning of hydrothermal power systems

In this paper, parallel processing techniques are employed to improve the performance of the stochastic dynamic programming applied to the long term operation planning of electrical power system. The hydroelectric plants are grouped into energy equivalent reservoirs and the expected cost functions are modeled by a piecewise linear approximation, by means of the Convex Hull algorithm. In order to validate the proposed methodology, data from the Brazilian electrical power system is utilized.