Showing papers on "Economic dispatch published in 2000"

A homogeneous linear programming algorithm for the security constrained economic dispatch problem

Abstract: This paper presents a study of the simplified homogeneous and self-dual (SHSD) linear programming (LP) interior point algorithm applied to the security constrained economic dispatch (SCED) problem. Unlike other interior point SCED applications that consider only the N security problem, this paper considers both (N-1) and (N-2) network security conditions. An important feature of the optimizing interior point LP algorithm is that it can detect infeasibility of the SCED problem reliably. This feature is particularly important in SCED applications since line overloading following a contingency often results in an infeasible schedule. The proposed method is demonstrated on the IEEE 24 bus test system and a practical 175 bus network. A comparison is carried out with the predictor-corrector interior point algorithm for the SCED problem presented previously (see ibid., vol. 12, no.2, p.803-10, 1997).

New approach with a Hopfield modeling framework to economic dispatch

Abstract: This paper presents a new Hopfield model based approach for the economic dispatch problem of power systems. To solve the economic dispatch problem using the Hopfield model, an energy function composing power mismatch, total fuel cost and the transmission line losses is defined. The weighting factors associated with the terms of the energy function can be either appropriately selected or directly estimated in the proposed model. Which, however, are determined by trial and error in the conventional Hopfield method. To minimize the value of the energy function, the computational procedures including a series of adjusting the weighting factor associated with the transmission line losses and updating the unit generations and power losses are carried out. Because the weighting factors are governed by some relationships developed, adjustment of the weighting factor is much simpler and more effective in steadily achieving solutions than adjustment of the /spl lambda/-multiplier in the lambda-iteration method for economic dispatch problems. Computational results reveal that this approach can find accurate solutions more simply and fast compared with the conventional lambda-iteration method.

Assessment of available transfer capability of transmission systems

Abstract: The available transfer capability (ATC) of a transmission system is a measure of unutilized capability of the system at a given time and depends on a number of factors such as the system generation dispatch, system load level, load distribution in the network, power transfers between areas, network topology, and the limits imposed on the transmission network due to thermal, voltage and stability considerations. This paper describes a method for determining the ATC between any two locations in a transmission system (single-area or multiarea) under a given set of system operating conditions. The method also provides ATCs for selected transmission paths between the two locations in the system and identifies the most limiting facilities in determining the network's ATC. In addition, the method can be used to compute multiple ATCs between more than one pair of locations. The proposed method is illustrated using the IEEE reliability test system (RTS).

Decomposition model and interior point methods for optimal spot pricing of electricity in deregulation environments

Abstract: In this paper, an integrated optimal spot pricing model is presented first. The proposed model includes the detailed derivation of optimal nodal specific real-time prices for active and reactive powers, and the method to decompose them into different components corresponding to generation, loss, and many selected ancillary services such as spinning reserve, voltage control and security control. The features of the proposed model are discussed in relationship to existing pricing models and classical economic dispatch. The model is then implemented by modifying existing Newton OPF methods through interior point algorithms, which can effectively avoid "go" "no go" gauge (i.e. highly volatile) in the calculation of spot prices. Case studies on 5-bus and IEEE 30-bus systems are reported to illustrate the proposed method.

Real-time dispatch of trams in storage yards

Abstract: Real-time dispatch problems arise when preparing and executing the daily schedule of local transport companies. We consider the daily dispatch of transport vehicles like trams in storage yards. Immediately on arrival, each tram has to be assigned to a location in the depot and to an appropriate round trip of the next schedule period. In order to achieve a departure order satisfying the scheduled demand, shunting of vehicles may be unavoidable. Since shunting takes time and causes operational cost, the number of shunting movements should be minimized without violation of operational constraints. As an alternative, we may serve some round trips with trams of type differing from the requested type. In practice, the actual arrival order of trams may differ substantially from the scheduled arrival order. Then, dispatch decisions are due within a short time interval and have to be based on incomplete information. For such real-time dispatch problems, we develop combinatorial optimization models and exact as well as heuristic algorithms. Computational experience for real-world and random data shows that the derived methods yield good (often optimal) solutions within the required tight time bounds.

Feasibility assessment of simultaneous bilateral transactions in a deregulated environment

Abstract: A large number of transmission transactions is expected to take place with the introduction of competition into the electricity industry. These transactions need to be evaluated ahead of their scheduling time to check their feasibility with regard to the system conditions at the time of scheduling. Transmission system operators would have to honor and execute only transactions as far as the system design and system operating conditions permit. This paper describes a method for assessing the feasibility of simultaneous bilateral transactions with regard to the system economic dispatch and transmission system constraints. Transactions are classified into feasible and unfeasible. Feasible transactions can be accommodated without violating the system economic dispatch and transmission network constraints. Unfeasible transactions violate transmission network constraints and can not be accommodated fully without altering the system economic dispatch. The assessment method provides information on where and how much generation is to be rescheduled in order to accommodate an unfeasible transaction. Such information will be useful in deciding whether a particular unfeasible transaction is worth serving or not. The IEEE Reliability Test System (RTS) is used to illustrate the assessment method.

Allocation of FACTS devices in hydrothermal systems

Abstract: This work presents a methodology to represent and analyze the influence of FACTS (flexible AC transmission systems) devices on the multiperiod economic dispatch problem. Two FACTS devices are represented: the series compensator and the phase shifter. The aim is to find the best location of FACTS devices in order to minimize the expected thermal generation costs and the investments on these devices in a prespecified time interval. The methodology handles the operational interdependence between cascade hydro plants which characterize the hydrothermal coordination problem. Transmission losses and circuit capacity variation are also taken into consideration. The approach is tested in a small system and to the system of the southern region of Brazil in order to illustrate the application of the algorithm. Some wheeling transactions are also introduced to investigate their influence on the FACTS location. The results show the robustness of the approach while highlighting the main problems which need be investigated.

Evolutionary Programming-Based Multiarea Economic Dispatch with Tie Line Constraints

Abstract: This paper presents a new approach to include tie line constraints in multiarea economic dispatch problems by using evolutionary programming (EP). The proposed method always finds the global or near global optimum for small and reasonable-sized multiarea economic dispatch (MAED) problems. The inclusion of tie line constraints to MAED does not introduce any complexity in the approach. The applicability and validity of the proposed method is shown by implementing it on three example systems - 2, 4, and 14 areas - and their results are compared with those obtained by classical economic dispatch, network flow programming, and dynamic programming methods, respectively. The results show that the proposed method can serve as a potential tool for solving MAED problems.

Budget constrained planning to optimize power system reliability

Abstract: De-regulation and re-regulation are forcing electric utilities to become more cost conscious. At some utilities, this has manifested itself in drastically reduced capital budgets. At the same time, utilities are under great pressure to maintain (and even improve) system reliability. With reduced budgets, it becomes necessary to establish accept/reject criteria that best allocates the budget while obtaining the highest possible system reliability. This paper presents a Budget Constrained Planning method to handle this situation. This method formulates project approvals as a rigorous optimization problem and uses a marginal cost/benefit approach similar to economic dispatch. Budget Constrained Planning is applied to the 1999 discretionary projects fund at Ameren Corporation and results are discussed.

Lambda of Lagrangian relaxation solution to unit commitment problem

Abstract: The difference between the lambda values of the economic dispatch and the unit commitment problems is presented, based on the economic interpretation of the Lagrangian relaxation solution framework. Although both sets of lambdas represent marginal cost of electricity, the underlying assumptions on their computation in the two problems are different, as explained. Results of two case studies that support the above differences are presented.

A study of the homogeneous algorithm for dynamic economic dispatch with network constraints and transmission losses

Abstract: This paper presents a study of the homogeneous interior point (HIP) method for the economic dispatch problem that combines both independent blocks of constraints (generation demand balance, network flows) and coupling constraints (ramping) into a single optimization problem. By approximating the network constraints through the DC load flow, and the transmission losses through the B-matrix loss formula, the problem is reduced to a convex optimization problem that possesses nonlinear inequality constraints and free variables. The HIP algorithm is specialized in solving this problem, it yields either an approximate global optimum solution or detects possible infeasibility or unboundedness of the problem. The algorithm is tested on the IEEE 14, 30, 57, and 118 bus test systems dispatched over 10 half-hour intervals. The results show that the algorithm is practically efficient.

An analytical solution to the economic dispatch problem

Abstract: This letter treats the basic problem of economic operation of power systems and presents a mathematical derivation that proves that the classic economic dispatch (ED) problem, with quadratic-convex cost functions, can be solved analytically, i.e., without any approximations or need for numerical iterative optimization algorithms. Duality theory is employed to determine both the exact primal and exact dual solutions. All this requires, at most, are 2n function evaluations. It is stated, therefore, that the use of an ED model as an optimization-based electricity auction does not cause any conflict of interest.

Fast and accurate power dispatch using a relaxed genetic algorithm and a local gradient technique

Abstract: A relaxed hybrid genetic algorithm (RHGA) and gradient technique (GT) is proposed to economically allocate power generation in a fast, accurate, and relaxed manner. The proposed hybrid scheme is constructed in such a way that a GA performs a base-level search, makes rapid decisions to direct the local GT to quickly climb the potential hill. The proposed method further ensures the dispatch quality as well as speed by allowing a loose match between the power generation and the load demand at the base search, and compensates for any mismatch at the beginning of the local search. Consequently, a GA is able to deliver equal effort to the search for the least cost and power balance without the risk of attaining infeasible solutions. The effectiveness of the proposed RHGA is verified on two test cases. The first is the static economic dispatch (SED) on a three-generator system, for which the near optimal solution is found within a comparable short time. The second is the dynamic economic dispatch (DED) problem on the practical Northern Ireland Electricity (NIE) system, which has a total of 25 generator units. The simulation results obtained are very encouraging with regard to the computational time and production cost.

Solving the economic dispatch problem with an integrated parallel genetic algorithm

Abstract: The application of an integrated parallel genetic algorithm (GA) incorporating simulated annealing (SA) and tabu search (TS) techniques to the economic dispatch (ED) problem is reported in this paper. The integrated genetic algorithm is implemented in both parallel and cluster structures. The parallel computing platform is based on a network of interconnected personal computers (PC) using TCP/IP socket communication facilities. Results from a case study of determining the optimal loading of 13 generators using a network of ten Pentium II-350 computers are presented. The proposed approach has the potential to be applied to other power engineering problem such as unit commitment and maintenance scheduling.

Combined regression-fuzzy approach for short-term load forecasting

Abstract: Accurate load forecasting is of great importance for power system operation; it is the basis of economic dispatch, unit commitment, hydrothermal coordination, and system security analysis, among other functions. An approach based on combined regression method and fuzzy inference system is developed for short-term load forecasting. The multilinear regression model is applied to find a preliminary load forecast. In addition, the fuzzy inference system makes a load correction inference from historical information and past forecast load errors from a multilinear regression model to infer a forecast load error. Adding the inferred load error to the preliminary load forecast obtains a final forecast load. The effectiveness of the proposed approach to the short-term load forecasting problem is demonstrated by practical data from the Taiwan Power Company.

Chaotic optimization for economic dispatch of power systems

Abstract: By applying chaotic optimization, which uses the ergodicity, stochastic property, and regularity of chaotic motion, a new algorithm for solution economic dispatch of power systems is proposed in this paper. It utilizes payoff information of candidate solutions to evaluate their optimality without any special requests for target function, and can consider the loss of transmission and the valve point discontinuities which can't be solved by the traditional Lagr ange multiplier method, so the accuracy of solutions is improved. Moreover, comparison of this method with genetic algorithm is made. Simulation results show that chaotic optimization method for economic dispatch of power systems is not only fast, but also simple and effective.

An economic analysis of the self commitment of thermal units

Abstract: Given the load profile of an electricity market and the capabilities of the set of generators supplying power to that market, it is likely that at any given point in time, available supply will exceed demand. If only a subset of generators is required, some method is required to commit and de-commit generators. In the past, system operators have employed a centralized method of unit commitment. Deregulation of the electricity industry throws doubt on the continued suitability of this method due to fairness issues and availability of accurate cost data. This paper examines the performance of decentralized unit commitment, where dispatch of generators is determined by offer curves submitted into a spot market by power producers.

Constrained economic dispatch with prohibited operating zones: a Hopfield neural network approach

Abstract: The work explores the use of Hopfield neural network for a load dispatch problem in a power system. It is a constrained economic dispatch problem with prohibited operating zones. Yalcinoz and Short (1997) discussed a special methodology to improve the performance of Hopfield networks for solving the unconstrained economic dispatch problem. In this paper the improved Hopfield network is applied to the constrained economic dispatch problem. A new mapping process has been used and a computational method for obtaining the weights and biases is described using a slack variable technique for handling inequality constraints. Applying the proposed approach is demonstrated by a 15 unit system with 4 units having prohibited zones.

A hybrid method of GA and BP for short-term economic dispatch of hydrothermal power systems

Abstract: This paper proposed a fast synthetic genetic algorithm (FSGA). The algorithm has faster convergence speed and higher computation precision, and the number of individuals and populations decreased, respectively. To overcome long training time of back propagation (BP) algorithm, this paper combined FSGA with BP, and applied the hybrid method to short-term economic dispatch of hydrothermal power system. The simulation results demonstrate that the hybrid method is effective and training time is short.

Comparison of Simulation Algorithms for the Hopfield Neural Network: An Application of Economic Dispatch

Abstract: This paper is mainly concerned with an investigation of the suitability of Hopfield neural network structures in solving the power economic dispatch problem. For Hopfield neural network applications to this problem three important questions have been answered: what the size of the power system is; how efficient the computational method; and how to handle constraints. A new mapping process is formulated and a computational method for obtaining the weights and biases is described. A few simulation algorithms used to solve the dynamic equation of the Hopfield neural network are discussed. The results are compared with those of a classical technique, Hopfield neural network approaches and an improved Hopfield neural network approach [1].

A new economic dispatch algorithm for thermal unit generation scheduling in power system

Abstract: This paper presents a new ED (economic dispatch) algorithm for thermal unit generation scheduling in a power system, which guarantees the near optimal solution without reducing calculation speed. It is well known that the accuracy of the fuel cost function has a great influence on the accuracy of the ED solution. However, a roughly approximated quadratic function of the generation cost has generally been used due to the difficulties in dealing with a cost function reflecting the nonlinearity of the actual generator response. In this paper, a new method is proposed to improve both the accuracy and the calculation speed of the ED. By using the inverse incremental cost functions, the ED can be transformed into a simple optimization problem associated with an n-th order polynomial equation. The proposed method reduces the computation time with adaptability to any higher order generation cost functions. The proposed method is tested with sample systems, which shows that the proposed algorithm yields more accurate and economical results with high computation time.

Homogeneous interior point method for constrained power scheduling

Abstract: A method for solving the active power economic dispatch problem is presented. The problem is formulated as a convex program which allows the inclusion of a second-order network model, phase shifters and operational constraints. An accurate representation of the line losses is achieved through the second-order model. The problem is solved using a homogeneous interior point (HIP) algorithm. The HIP algorithm yields either an approximate global optimum or detects the possible infeasibility or unboundedness of the problem. Moreover, this algorithm does not require any skill for setting a proper starting point. The algorithm is tested on standard IEEE networks and on a practical network. Computational experience shows that the method is efficient.

An integrated tool for analysis of power system constraints in the Spanish electricity market

Abstract: The role of the system operator in the Spanish electricity market, as it started on January 1/sup st/ 1998, is to determine the technical feasibility of the generation dispatch provided by the market operator. The security criteria of the Spanish power system require that branch power flows and bus voltages are within their limits, not only in normal operating conditions but also when any credible contingency occurs. This paper presents an integrated tool for analysis of power system constraints in the Spanish electricity market. The components of this tool are: a power system scenarios builder; contingency analysis routines; and preventive dispatch algorithms (active and reactive power). The tool addresses separately the overloaded branches and the bus voltage violations. The performance of the tool is illustrated using an actual scenario of the Spanish power system.

Modeling utility-scale wind power plants, part 1: Economics

Abstract: As the worldwide use of wind turbine generators continues to increase in utility-scale applications, it will become increasingly important to assess the economic and reliability impact of these intermittent resources. Although the utility industry in the United States appears to be moving towards a restructured environment, basic economic and reliability issues will continue to be relevant to companies involved with electricity generation. This paper is the first of two that address modeling approaches and results obtained in several case studies and research projects at the National Renewable Energy Laboratory (NREL). This first paper addresses the basic economic issues associated with electricity production from several generators that include large-scale wind power plants. An important part of this discussion is the role of unit commitment and economic dispatch in production-cost models. This paper includes overviews and comparisons of the prevalent production-cost modeling met hods, including several case studies applied to a variety of electric utilities. The second paper discusses various methods of assessing capacity credit and results from several reliability-based studies performed at NREL.

Reactive load modeling impacts on nodal prices in pool model electricity markets

Abstract: This paper is concerned with the interpretation of the nodal prices in competitive electricity markets based on the Pool paradigm. Such prices are the byproducts of the optimization performed by the independent grid operator (IGO) to determine the centralized economic dispatch taking into account all transmission network and physical/operations constraints. The IGO implicitly takes into account congestion considerations in determining the centralized economic dispatch. Under the Pool paradigm, a system marginal price no longer exists and each bus may have a different real and reactive power nodal price due to line losses and congestion avoidance considerations that can arise when the limit of one or more constraints is reached. The objective is to explore the economic signals provided by these prices and effectively apply them in the design of markets and the rules of the road for these markets. The main focus of the paper is on the explicit evaluation of the impacts of the reactive load on the nodal real and reactive prices. The authors adopt a rather general model for reactive load in which the reactive power at each node is represented as an affine function of the real power at that node, i.e., the reactive load is the sum of a constant and a constant power factor component. This model includes, as special cases, the constant reactive load and the constant power factor load including the case of purely real load corresponding to unity power factor. They investigate the relationship between the real and reactive nodal prices and evaluate the impacts on them of the dual variables due to the various other physical/operations constraints in the system. They discuss the significance of the nodal price observations and the effective utilization in developing appropriate price signals in the Pool paradigm.

A novel unit commitment method considering various operation constraints

Abstract: This paper presents a novel unit commitment method in which some intricate constraints are considered, such as available transfer capability limitation (ATCL) of both lines and interfaces, network loss effects, and units' ramp rates. The network security constraints are checked by DC power flow. The key technique of the method is the combination of dynamic programming for one tentative running unit with economic dispatch for fulfilled load (EDFL). The distinct features of the method are monotonous convergence, considering more constraints and less computational requirements. Comparison of the proposed method with the Lagrangian relaxation approach demonstrates the effectiveness and the potential benefits of the proposed method for power system operation.