Expansion Planning Model Research Articles

A multiple objective linear programming model for power generation expansion planning

The planning of new units for electrical power generation is a problem which involves different and conflicting aspects. Besides cost, security issues and environmental concerns must be explicitly incorporated into the models. In this way mathematical models become more realistic, and they enhance the decision maker's comprehension of the complex and conflicting nature of the distinct aspects of the problem. A multiple objective linear programming model for power generation expansion planning is presented. The model considers three objective functions (net present cost of the expansion plans, reliability of the supply system, and environmental impacts) and three categories of constraints (load requirements, operational restrictions and budget). Three generating technologies are considered for power system expansion: oil, nuclear and coal.

Evaluating risk management strategies in resource planning

This paper discusses the evaluation of risk management strategies as a part of integrated resource planning. Value- and scope-related uncertainties can be addressed during the process of planning, but uncertainties in the operating environment require technical analysis within planning models. Flexibility and robustness are two key classes of strategies for managing the risk posed by these uncertainties. This paper reviews standard capacity expansion planning models and shows that they are poorly equipped to compare risk management strategies. Those that acknowledge uncertainty are better at evaluating robustness than flexibility, which implies a bias against flexible options. Techniques are available to overcome this bias.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

CHOPIN, a heuristic model for long term transmission expansion planning

This paper describes the long term transmission expansion planning model CHOPIN. In CHOPIN, the network expansion is formulated as the static optimization problem of minimizing the global annual cost of electricity production, which is obtained as the sum of the annualized network investment cost, the operation cost and the reliability cost. The solution method takes advantage of the natural decomposition between the investment and operation submodels. The investment submodel is solved by a new heuristic procedure that in practice has invariably yielded the optimal plan. At the operation level CHOPIN optimizes over a multiplicity of scenarios which are characterized by the demand, the hydraulicity and the availability of components. The network is represented by any one out of four options: DC load flow (DCLF), transportation model and two hybrid models. Any of these models may consider the ohmic losses. The model is very efficient computationally; this fact was verified on rest examples, as well as on the actual transmission expansion planning of the Spanish system. >

The nuclear option for US electrical generating capacity additions utilizing boiling water reactor technology

The technology status of the advanced boiling water reactor (ABWR) and the simplified boiling water reactors (SBWR) is presented along with an analysis of the economic potential of advanced nuclear power generation systems based on BWR technology to meet the projected domestic electrical generating capacity need through 2005. The forecasted capacity needs are determined for each domestic North American Electric Reliability Council (NERC) region. Extensive data sets detailing each NERC region's specific generation and load characteristics, and capital and fuel cost parameters are utilized in the economic analysis, by means of an expansion planning model, of the optimal generation additions required to meet this need. In addition to a reference case, several sensitivity studies are performed with regard to capital costs and fuel price escalation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

4.4. Dynamic programming models

The use of dynamic programming in system expansion planning models is discussed. Dynamic programming is a very powerful technique for solving optimization problems. A brief overview of the dynamic programming methodology is presented along with an example of how dynamic programming was applied in a model developed for electric system expansion planning.

An optimization model for long-range transmission expansion planning

A static network synthesis method for transmission expansion planning is presented. The static synthesis problem is formulated as a mixed-integer network flow model that is solved by an implicit enumeration algorithm. This model considers as the objective function the most productive trade-off, i.e. the one resulting in low investment costs and good electrical performance. The load and generation nodal equations are considered in the constraints of the model. The power transmission law of DC load flow is implicit in the optimization model. Results of computational tests are presented, showing the advantage of this method compared with a heuristic procedure. The case studies provide a comparison of computation times and costs of solutions obtained for the Brazilian North-Northeast transmission system. >

A continuous linear optimization model for the exact solution of travelling-salesman-problems in connexion with expansion planning of ring networks

This work describes a subproblem in connexion with a newly developed optimization model for dynamic expansion planning of ring networks serving for electric power distribution in urban supply areas. This subproblem is the exact solution of a Travelling-salesman-problem by a continuous linear optimization model. A short survey over the complete planning model is given too. The model is created by a problem specific, flexibly applicable matrix generator and solved by a powerful commercial standard programming package. The symmetric Travelling-salesman-problems under consideration are characterized as follows: The set of potential ways is determined by the public streets of a city and the nodes to be connected are distributed uniformly over the supply area. The new optimization model allows the exact solution of problems up to about 60 nodes. The practical application is demonstrated by two examples.

A dynamic model for generation expansion planning

Selection of optimal size and optimal timing of addition of (new) generators are the two basic problems in generation expansion planning. In this paper we have developed a simple mathematical model for generation expansion planning which consists of an economic indicator (cost functional) and a dynamic model relating future expansion with the existing capacity and the retirement characteristics of generating units available on the market. For illustration, the proposed model has been applied to a hypothetical example of a utility and gives encouraging results.

Maintenance Scheduling Under Uncertainty

This paper introduces an extension of maintenance scheduling concepts to incorporate short-term load forecast uncertainty. Maintenance schedules thus derived are much more realistic for generation expansion planning models because they more accurately reflect decisions made during system operation. The method proposed arranges the maintenance schedule to level the risk exposure under uncertain weather outcomes with only a modest amount of revision of existing maintenance scheduling programs which level risk.

Long range stochastic planning of generation considering overdesign

This paper presents a new model for the optimal expansion planning of generation facilities in Power Systems under uncertainties of demand forecasts and generator outages. The objective is to find an expansion strategy requiring minimum present worth of revenue requirements so that electric power can be supplied to consumers at a reasonably low price with high degree of reliability. System utility is evaluated in terms of its capacity to meet demand requirements under uncertain conditions. The design also aims at reducing the over design of the system which requires a large capital outlay. A method based on the preference order dynamic programming is presented to determine the long-range optimal expansion strategy. This avoids the drawbacks of the conventional dynamic programming methods and requires lesser number of alternatives to be considered for selection of the optimal expansion policy.

A Model for Expansion Planning of Transmission Systems A Practical Application Example

This paper presents a model for transmission planning as well as its application to the 230 KV underground network for the Mexico City Metropolitan Area.

A mathematical model for long range expansion planning of generation and transmission in electric utility systems

This paper provides a mathematical model (linear mixed integer program) for the problem of selecting an expansion plan over a planning horizon for an electric utility system. The objective function that is chosen is the minimization of the net present value of the capital investment cost associated with the construction of power plants and transmission lines plus the operating costs of the system. The restrictions associated with the problem are the requirement to satisfy the forecasted demands of the systems for electrical energy plus the physical restrictions that result from having limited capital resources and plant site limitations. The model provides construction expansion schedules for power plants and transmission lines (i.e. what capacity to build, where the additional capacity is to be located, and when it is to be completed). Additionally, an approximate operating schedule for plants and transmission lines is provided. An application of the modeling technique to a regional electrical utility system illustrating the formulation methods and the results that can be obtained is given.