Feed- Forward Neural Network based Day Ahead Nodal Pricing

An electricity locational marginal pricing prediction normally recognized by 24-hour day-ahead nodal price forecast. In this paper first collected all physical and technical data i.e. availability of generation and their cost characteristics, real and reactive demands at various buses, transmission capacity availability at various conditions like peak and off-peak conditions. All these input data are used as input for computation of optimal power flow. The nodal prices are calculated with AC-DC optimal power flow methodology for IEEE 30 bus system. The resulted optimal real electricity bus voltages, nodal prices, reactive and real demands, angles have been given as inputs to Artificial Neural Network (ANN) for predict day ahead nodal prices.

Model-Based Identification of Alternative Bidding Zones: Applications of Clustering Algorithms with Topology Constraints

The definition of bidding zones is a relevant question for electricity markets. The bidding zones can be identified starting from information on the nodal prices and network topology, considering the operational conditions that may lead to congestion of the transmission lines. A well-designed bidding zone configuration is a key milestone for an efficient market design and a secure power system operation, being the basis for capacity allocation and congestion management processes, as acknowledged in the relevant European regulation. Alternative bidding zone configurations can be identified in a process assisted by the application of clustering methods, which use a predefined set of features, objectives and constraints to determine the partitioning of the network nodes into groups. These groups are then analysed and validated to become candidate bidding zones. The content of the manuscript can be summarized as follows: (1) A novel probabilistic multi-scenario methodology was adopted. The approach needs the analysis of features that are computed considering a set of scenarios defined from solutions in normal operation and in planned maintenance cases. The weights of the scenarios are indicated by TSOs on the basis of the expected frequency of occurrence; (2) The relevant features considered are the Locational Marginal Prices (LMPs) and the Power Transfer Distribution Factors (PTDFs); (3) An innovative computation procedure based on clustering algorithms was developed to group nodes of the transmission electrical network into bidding zones considering topological constraints. Several settings and clustering algorithms were tested in order to evaluate the robustness of the identified solutions.

Estimating the cost of heat generation and consumption in district heating systems

The pricing of thermal energy is an important component of the efficient operation of the heat supply system. The article deals with the calculation of the cost of heat for consumers and producers of heat as based on the optimization problem of operation modes of the heat supply system with its further reduction to the conditions of optimality. The latter is to be achieved on the basis of the Lagrange function, with undetermined Lagrange multipliers obtained in the calculation process to be interpreted as nodal (marginal) prices of heat. This approach allows one to determine the pricing at each node. Based on the calculation of nodal prices of heat we determine the cost of heat transportation. Backed by the methodological tools developed, we have performed a demonstration of the calculation of nodal prices of heat and developed an algorithm for calculation of nodal prices of heat generation and consumption and overall technical and economic performance indicators of the heat supply system.

Calculation of Nodal Prices for Heat Energy in Heat Supply Systems

The article is devoted to the calculation of nodal prices for heat energy in heat supply systems. The problem, mathematical model and method of calculating nodal prices of heat energy for all consumers of the heat supply system considered, taking into account the different cost of heat production by sources, optimal flow distribution, and placement of consumers in the heat network (distance from the source). As the main computational tool for calculating nodal prices for heat energy, the Lagrange multiplier method used in the problem of modes optimizing in heat supply system, which allows explaining in detail the formation of the price for heat energy in each node. With the help of the proposed methodological support, practical research has been carried out for real heat supply system.

Development of methods for modeling dynamic thermo-hydraulic conditions for assessing the quality of functioning of heat supply systems

A simulation dynamic model of thermo-hydraulic conditions of heat supply systems (HSS) is presented. The model makes it possible to analyze in time HSS operating conditions with arbitrary configuration and structure, dissimilar loads of heat consumers, taking into account the transport lag of the coolant, cooling along the length of the pipelines, under different weather conditions, disturbances in the system and a given control scenario in the control nodes. To assess the quality, indicators of the degree of heat supply to consumers are proposed. Formulas are given for determining the total, average and average expected deficit (excess) of heat, as well as heat losses in the network, for a calculated period of time under the given control rules. It is proposed to evaluate the efficiency of the operating conditions by the coefficient of efficient use of energy for the billing period. To take into account the real cost of heat, a mathematical model and a method for calculating nodal prices are presented.