Unit commitment problem in electrical power production

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The unit commitment problem (UC) in electrical power production is a large family of mathematical optimization problems where the production of a set of electrical generators is coordinated in order to achieve some common target, usually either matching the energy demand at minimum cost or maximizing revenue from electricity production. This is necessary because it is difficult to store electrical energy on a scale comparable with normal consumption; hence, each (substantial) variation in the consumption must be matched by a corresponding variation of the production.

Contents

Coordinating generation units is a difficult task for a number of reasons:

Because the relevant details of the electrical system vary greatly worldwide, there are many variants of the UC problem, which are often very difficult to solve. This is also because, since some units require quite a long time (many hours) to start up or shut down, the decisions need be taken well in advance (usually, the day before), which implies that these problems have to be solved within tight time limits (several minutes to a few hours). UC is therefore one of the fundamental problems in power system management and simulation. It has been studied for many years, [1] [2] and still is one of the most significant energy optimization problems. Recent surveys on the subject [3] [4] count many hundreds of scientific articles devoted to the problem. Furthermore, several commercial products comprise specific modules for solving UC, such as MAON [5] and PLEXOS [6] , or are even entirely devoted to its solution. [7]

Elements of unit commitment problems

There are many different UC problems, as the electrical system is structured and governed differently across the world. Common elements are:

The decisions that have to be taken usually comprise:

While the above features are usually present, there are many combinations and many different cases. Among these we mention:

Management objectives

The objectives of UC depend on the aims of the actor for which it is solved. For a MO, this is basically to minimize energy production costs while satisfying the demand; reliability and emissions are usually treated as constraints. In a free-market regime, the aim is rather to maximize energy production profits, i.e., the difference between revenues (due to selling energy) and costs (due to producing it). If the GenCo is a price maker, i.e., it has sufficient size to influence market prices, it may in principle perform strategic bidding [12] in order to improve its profits. This means bidding its production at high cost so as to raise market prices, losing market share but retaining some because, essentially, there is not enough generation capacity. For some regions this may be due to the fact that there is not enough grid network capacity to import energy from nearby regions with available generation capacity. [13] While the electrical markets are highly regulated in order to, among other things, rule out such behavior, large producers can still benefit from simultaneously optimizing the bids of all their units to take into account their combined effect on market prices. [14] On the contrary, price takers can simply optimize each generator independently, as, not having a significant impact on prices, the corresponding decisions are not correlated. [15]

Types of production units

In the context of UC, generating units are usually classified as:

Electrical grid models

There are three different ways in which the energy grid is represented within a UC:

When the full AC model is used, UC actually incorporates the optimal power flow problem, which is already a nonconvex nonlinear problem.

Recently, the traditional "passive" view of the energy grid in UC has been challenged. In a fixed electrical network currents cannot be routed, their behavior being entirely dictated by nodal power injection: the only way to modify the network load is therefore to change nodal demand or production, for which there is limited scope. However, a somewhat counter-intuitive consequence of Kirchhoff laws is that interrupting a line (maybe even a congested one) causes a global re-routing of electrical energy and may therefore improve grid performances. This has led to defining the Optimal Transmission Switching problem, [11] whereby some of the lines of the grid can be dynamically opened and closed across the time horizon. Incorporating this feature in the UC problem makes it difficult to solve even with the DC approximation, even more so with the full AC model. [23]

Uncertainty in unit commitment problems

A troubling consequence of the fact that UC needs be solved well in advance to the actual operations is that the future state of the system is not known exactly, and therefore needs be estimated. This used to be a relatively minor problem when the uncertainty in the system was only due to variation of users' demand, which on aggregate can be forecasted quite effectively, [24] [25] and occurrence of lines or generators faults, which can be dealt with by well established rules (spinning reserve). However, in recent years the production from intermittent renewable production sources has significantly increased. This has, in turn, very significantly increased the impact of uncertainty in the system, so that ignoring it (as traditionally done by taking average point estimates) risks significant cost increases. [22] This had made it necessary to resort to appropriate mathematical modeling techniques to properly take uncertainty into account, such as:

The combination of the (already, many) traditional forms of UC problems with the several (old and) new forms of uncertainty gives rise to the even larger family of Uncertain Unit Commitment [4] (UUC) problems, which are currently at the frontier of applied and methodological research.

Integrated Transmission and Distribution Models

One of the major issues with the real-time unit commitment problem is the fact that the electricity demand of the transmission network is usually treated as a "load point" at each distribution system. The reality, however, is that each load point is a complex distribution network with its own sub-loads, generators, and DERs. By simplifying a distribution into load points can lead to extreme operational troubles of the whole power grid. Such problems include high pressure on the power transmission system and reverse power flow from the distribution systems towards the power transmission system. A newly pursued approach for more effectively solving the unit-commitment problem hence is born by Integrated Transmission and Distribution Systems. [26] In such models, the unit commitment problem of the Transmission Systems is usually combined with the Renewable Management Problem of the Distribution Systems by the means of bi-level programming tools.

See also

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