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| {{Refimprove|date=July 2007}}
| | Alyson is the name individuals use to call me and I think it sounds quite good when you say it. Mississippi is the only place I've been residing in but I will have to transfer in a year or two. I am an invoicing officer and I'll be promoted quickly. The preferred hobby for him and his kids is to perform lacross and he would by no means give it up.<br><br>Here is my weblog ... [http://help.ksu.edu.sa/node/65129 love psychic readings] |
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| '''Economic dispatch''' is the short-term determination of the optimal output of a number of [[electricity generation]] facilities, to meet the system load, at the lowest possible cost, subject to transmission and operational constraints. The Economic Dispatch Problem is solved by specialised computer software which should honour the operational and system constraints of the available resources and corresponding transmission capabilities. In the US [[Energy Policy Act of 2005]] the term is defined as "the operation of generation facilities to produce energy at the lowest cost to reliably serve consumers, recognising any operational limits of generation and transmission facilities"<ref>[http://web.archive.org/web/20110429035824/http://www.doi.gov/pam/EnergyPolicyAct2005.pdf Energy Policy Act 2005].</ref>
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| The main idea is that in order to serve load at minimum total cost, the set of generators with the lowest marginal costs must be used first, with the marginal cost of the final generator needed to meet load setting the system marginal cost. This is the cost of delivering one additional MW of energy onto the system. The historic methodology for economic dispatch was developed to manage fossil fuel burning power plants, relying on calculations involving the input/output characteristics of power stations.
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| ==Basic Mathematical Formulation<ref>{{cite book|last=Kirschen|first=Daniel|title=Fundamentals of Power System Economics|year=2010|publisher=Wiley|isbn=0-470-84572-4}}</ref> ==
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| The economic dispatch problem can be thought of as maximising the economic welfare {{math|''W''}} of a power network whilst meeting system constraints. For a network with {{math|''n''}} buses (nodes), where {{math|''I''<sub>''k''</sub>}} represents the net power injection at bus {{math|''k''}}, and {{math|''C''<sub>''k''</sub>(''I''<sub>''k''</sub>)}} is the cost function of producing power at bus {{math|''k''}}, the unconstrained problem is formulated as:
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| :<math>\min_{I_k}\; (-W)=\min_{I_k}\;\left \{ \sum_{k=1}^n C_k(I_k)\right \}</math>
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| Constraints imposed on the optimisation are the need to maintain a power balance, and that the flow on any line must not exceed its capacity. For the power balance, the sum of the net injections at all buses must be equal to the power losses in the branches of the network:
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| :<math> \sum_{k=1}^n I_k = L(I_1,I_2,\dots,I_{n-1})</math>
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| The power losses {{math|''L''}} depend on the flows in the branches and thus on the net injections as shown in the above equation. However it cannot depend on the injections on all the buses as this would give an over-determined system. Thus one bus is chosen as the [[Slack bus]] and is omitted from the variables of the function {{math|''L''}}. The choice of Slack bus is entirely arbitrary, here bus {{math|''n''}} is chosen.
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| The second constraint involves capacity constraints on the flow on network lines. For a system with {{math|''m''}} lines this constraint is modelled as:
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| :<math> F_l(I_1,I_2,\dots,I_{n-1}) \leq F_{l}^{max} \qquad l=1,\dots,m</math>
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| where {{math|''F''<sub>''l''</sub>}} is the flow on branch {{math|''l''}}, and {{math|''F''<sub>''l''</sub><sup>''max''</sup>}} is the maximum value that this flow is allowed to take. Note that the net injection at the slack bus is not included in this equation for the same reasons as above.
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| These equations can now be combined to build the [[Lagrange multiplier|Lagrangian]] of the optimization problem:
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| :<math> \mathcal{L}= \sum_{k=1}^n C_k(I_k) + \pi \left [ L(I_1,I_2,\dots,I_{n-1})-\sum_{k=1}^n I_k \right ] + \sum_{l=1}^m \mu_l \left [ F_{l}^{max}-F_l(I_1,I_2,\dots,I_{n-1}) \right ]</math>
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| where π and μ are the Lagrangian multipliers of the constraints. The conditions for optimality are then:
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| :<math> {\partial \mathcal{L}\over\partial I_k} = 0 \qquad k=1,\dots,n </math>
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| :<math> {\partial \mathcal{L}\over\partial \pi} = 0 </math>
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| :<math> {\partial \mathcal{L}\over\partial \mu_l} = 0 \qquad l=1,\dots,m </math>
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| :<math> \mu_l \cdot \left [ F_{l}^{max}-F_l(I_1,I_2,\dots,I_{n-1}) \right ] = 0 \quad \mu_l \geq 0 \quad k=1,\dots,n </math>
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| where the last condition is needed to handle the inequality constraint on line capacity.
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| Solving these equations is computationally difficult as they are nonlinear and implicitly involve the solution of the [[Power flow study|power flow]] equations. The analysis can be simplified using a linearised model called a DC power flow.
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| ==References==
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| {{Reflist}}
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| ==External links==
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| * [http://www.ferc.gov/EventCalendar/Files/20051110172953-FERC%20Staff%20Presentation.pdf Economic Dispatch: Concepts, Practices and Issues]
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| [[Category:Electric power]]
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| [[Category:Production and manufacturing]]
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Alyson is the name individuals use to call me and I think it sounds quite good when you say it. Mississippi is the only place I've been residing in but I will have to transfer in a year or two. I am an invoicing officer and I'll be promoted quickly. The preferred hobby for him and his kids is to perform lacross and he would by no means give it up.
Here is my weblog ... love psychic readings