Electricity markets: transmission prices methods

In the context of electricity markets, transmission pricing is an important tool to achieve an efficient operation of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for this reason transmission tariffs must follow strict criteria. This paper presents the following methods to tariff the use of transmission networks by electricity market players: Post-Stamp Method; MW-Mile Method Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price. A nine bus transmission network is used to illustrate the application of the tariff methods.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

A real time pricing approach to deal with excessive wind power situations

The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Transmission price simulator in a liberalized electricity market

This paper presents a software tool (SIM_CMTP) that solves congestion situations and evaluates the taxes to be paid to the transmission system by market agents. SIM_CMTP provides users with a set of alternative methods for cost allocation and enables the definition of specific rules, according to each market and/or situation needs. With these characteristics, SIM_CMTP can be used as an operation aid for Transmission System Operator (TSO) or Independent System Operator (ISO). Due to its openness, it can also be used as a decision-making support tool for evaluating different options of market rules in competitive market environment, guarantying the economic sustainability of the transmission system.

Transmission costs allocation based on optimal re-dispatch

Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Transmission tariffs in competitive electricity markets

In context of electricity market, the transmission price is an important tool to an efficient development of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for that reason evaluate tariff must have strict criterions. This paper explains several methodologies to tariff the use of transmission network by transmission network users. The methods presented are: Post-Stamp Method; MW-Mile Method; Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price.

Transmission cost allocation using cooperative game theory: a comparative study

In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

Nodal price simulation in competitive electricity markets

Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.