Lubov Petrichenko

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.

Stochastic planning of distribution lines

The distribution line planning task has become more complex due to several impacting factors. This paper presents a stochastic approach for implementing an optimization procedure with a statistical representation of the electricity prices, ambient temperature and load currents in the distribution network. The validation of this stochastic approach is based on the comparison results of both examined approaches (stochastic and deterministic), which are applied for the computation of the total average annual costs. Attention has been focused on reducing total average annual costs by optimizing the conductor profile of a power line and the transformer capacity. Thus, the Net Present Value of the total average annual costs can be evaluated during the planning period. The problem is formulated as a minimization of the Net Present Value of the total average annual costs of an examined distribution line project. The tool is implemented in MATLAB software by using the Monte Carlo method. The proposed stochastic approach has been applied in the solution of an example of a distribution line project, which is presented.

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.

Impact of smart electric thermal storage on distribution grid

The paper presents a preliminary assessment on impact of smart electric storage heating on distribution grid in comparison to conventional electric heating if heating electrification is partly introduced. Real-world data of electric load, heating demand, electricity prices and ambient temperature was used for simulations to conclude that while a small penetration of smart storage heating can facilitate efficient usage of the existing distribution grid, larger penetrations can require grid reinforcements due to a significantly increased electric load. These effects could be partly mitigated using smart charging algorithms for storage heaters. From the economic point of view, smart storage heating provides cheaper energy for end-users and lower cost of distribution losses for the system operator.

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.