Viktoria Neimane

Using Standard Deviation as a Measure of Increased Operational Reserve Requirement for Wind Power

The variability inherent in wind power production will require increased flexibility in the power system, when a significant amount of load is covered with wind power. Standard deviation (σ) of variability in load and net load (load net of wind) has been used when estimating the effect of wind power on the short term reserves of the power system. This method is straightforward and easy to use when data on wind power and load exist. In this paper, the use of standard deviation as a measure of reserve requirement is studied. The confidence level given by ±3–6 times σ is compared to other means of deriving the extra reserve requirements over different operating time scales. Also taking into account the total variability of load and wind generation and only the unpredicted part of the variability of load and wind is compared. Using an exceedence level can provide an alternative approach to confidence level by standard deviation that provides the same level of risk. The results from US indicate that the number of σ that result in 99% exceedence in load following time scale is between 2.3–2.5 and the number of σ for 99.7% exceedence is 3.4. For regulation time scale the number of σ for 99.7 % exceedence is 5.6. The results from the Nordic countries indicate that the number of σ should be increased by 67–100% if better load predictability is taken into account (combining wind variability with load forecast errors).

On Co-generation Strategies in the Cities of North-Eastern Europe

The high potential for utilization of co-generation power plants in the cities of North-Eastern Europe is illustrated in this paper. The features associated with climatic and economic factors are analyzed. The paper describes the methods for demand forecasting used in the case study and the chosen criteria and methods for economic assessment of different energy supply alternatives. The results of economic assessment support the decision about the optimal placement and parameters of CHPs, including small scale CHPs. Application of cooperative Game theory in order to support the decision-making in the market environment is described and demonstrated on the real life case study.

Stochastic optimization of power line design

During the recent years, power industries have been facing significant changes due to deregulation and liberalization of the energy markets and increase of the installed capacity of renewable energy sources. These factors directly affect the transmission network planning (TNP) task and inspire a search for new, more adequate methods. This paper compares a deterministic method - the economic intervals (EI) method - and the stochastic approach based (SAB) method. Both methods are used for designing the overhead power line (OHPL), choosing the optimum conductor type and cross-section as well as other main line parameters such as the height, type and coordinates of towers, the line route, the line fittings, etc. Moreover, the paper presents a new approach for implementing a stochastic optimization procedure with a statistical representation of the electricity prices, ambient temperature and load currents in the transmission network. The problem is formulated as minimization of the total annual costs for the transmission line (TL) construction project. The tool is implemented in MATLAB software by using the Monte Carlo (MC) method as well as in OHPL designing software - PLSCADD.

The stochastic approach for conductor selection in transmission line development projects

A stochastic approach is proposed for selecting the overhead line cross-sections that would be optimal taking into account the electricity market conditions. For this purpose, several conductor types with different conductor cross-sections were considered including the High Temperature Low Sag conductor types such as ACCC and ACCR, which are a part of the advanced technology. The total capital costs depending on the technical aspects were estimated as well. The paper proposes a method that minimizes the average value of the annual costs for the construction of a line based on a statistical representation of the electric power prices, the ambient temperature and the electrical current loads in the electrical networks. The use of the Monte-Carlo method and the mentioned statistical data allow the synthesis of a user-friendly algorithm to solve this problem. As an example of the stochastic approach, the 330 kV transmission line was selected. The solution tasks are done in the MATLAB and “SAPR LEP” software.

Approach for energy supply system planning based on cooperative game theory

This paper is dedicated to the task of energy supply system planning in the market environment. The possibilities of forming coalitions between companies are considered. In this case, for justifying the decisions and distributing the gains a cooperative game theory is used. Methods of forming a coalition and distributing additional gains are described in this paper. The examples from heat supply planning and planning new network connections show the rationality and efficiency of using the considered approach.

A stochastic approach to the feasibility study for overhead power lines

This paper presents a stochastic optimization approach to the feasibility study for power lines, taking into account market conditions. To validate the proposed stochastic approach, an economic comparison of several power line design alternatives has been done, considering technical issues as well. The final evaluation and analysis was based on the results obtained by applying both approaches: the deterministic (classical) method and the stochastic one. Both methods are used for power line design including optimum selection of the main parameters of the line such as tower height, type and coordinates, conductor type and cross-section, line fittings etc. The optimization problem is formulated as minimization of the total annual operating and construction costs. The solution task is realized in MATLAB software by using the Monte Carlo method as well as in the overhead power line automation design system PLS-CADD.

Probabilistic method for selection of power line wire type and cross-section

The paper presents a comparison of two methodologies for selection of overhead line wire type and cross-section considering market conditions. All existing methodologies which are used to determine optimal cross-section for transmission line wires can be divided into two categories: deterministic and probabilistic (stochastic). This paper presents a new approach for stochastic optimization and compares it to simplified deterministic approach. The proposed method minimizes total annual exploitation and construction costs of the transmission line based on utilization of existing large and easy accessible databases (electricity prices, ambient temperature, load records). The use of the Monte Carlo methods base and above-mentioned databases allows designing a user-friendly algorithm to solve this problem.

Designing a transmission line using Pareto approach

Transmission networks are facing an investment challenge due to the limited capacity of the existing power lines. Construction of the new overhead lines is associated with several legal, technical and economic problems. This paper describes Pareto approach for choosing the optimum design of the power line by minimizing the invested capital costs and maximizing the net present value. The analysis of presented solution including assessment of technical and economic efficiency is based on the model of a real line project. The results of the analysis are discussed in the paper.