Michał Warchoł

Heat Accumulator in Large District Heating Systems: Simulation and Optimisation

Heat accumulators in large district heating systems are used to buffer heat production. Their main purpose is to make heat production as independent as possible from district heating system demand. To do this effectively a heat accumulator of appropriate capacity must be selected. In large district heating systems, heat accumulators can be used for equalising production over periods lasting a few hours. Accumulators can be used for optimising electricity and heat production to achieve possible highest income. It may be important in situations where on-line prices change. An optimising algorithm for heat accumulator use is shown and commented. Typical working situations are simulated and results presented.Copyright

New Improvements of Immune Inspired Optimizer SILO

The article presents new improvements of an immune inspired optimization method, used to control a combustion process in a steam generating, coal fired, large scale boiler. Immune Inspired Optimizer SILO is implemented at each of three units of Ostroleka Power Plant (Poland) and at one unit in Newton Power Plant (USA). The results from Newton Power Plant are presented. They confirm that presented solution is effective and usable in practice and it can be treated as a good alternative to MFC controllers. The main goal of this solution is CO and NOx emission minimization.

Transition state layer in the immune inspired optimizer

The SILO (Stochastic Immune Layer Optimizer) system is a novel, immune inspired solution for an on-line optimization of a largescale industrial processes. Three layers of optimization algorithm were presented in previous papers. Each layer represents a different strategy of steady state optimization of the process. New layer of the optimization algorithm is presented in this paper. The new Transition State layer is responsible for efficient operation of the optimization system during essential process state transitions. New results from SILO implementation in South Korean power plant are presented. They confirm high efficiency of the SILO optimizer in solving technical problems.

The method for optimisation of gas compressors performance in gas storage systems

We present a computational method for achieving an optimal operation of compressor units used in industrial gas storage systems. The proposed method is capable to operate with a mix of compressor types (i.e., with different operational parameters, different power drives, and different types of construction, e.g., reciprocal and turbocompressors). The goal of the optimisation is to find an optimal compressors configuration and distribution of the compressor loads for each instance of time. The proposed method is based on conversion of a multidimensional discrete-continuous optimisation problem into a set of independent combinatorial and nonlinear optimisation problems. We derive the mathematical foundations of the algorithms. The exemplary results of the application are presented. [Received: May 4, 2016; Accepted: December 2, 2016]

Conditioning of Model Identification Task in Immune Inspired Optimizer SILO

Methods which provide good conditioning of model identification task in immune inspired, steady‐state controller SILO (Stochastic Immune Layer Optimizer) are presented in this paper. These methods are implemented in a model based optimization algorithm. The first method uses a safe model to assure that gains of the process’s model can be estimated. The second method is responsible for elimination of potential linear dependences between columns of observation matrix. Moreover new results from one of SILO implementation in polish power plant are presented. They confirm high efficiency of the presented solution in solving technical problems.

Software Environment for Distributed Simulation of Complex Systems

Abstract The paper is concerned with simulation of complex systems. A simulation using distributed computing by decomposing the simulation application into a set of concurrently executing processes is proposed as an alternative to traditional sequential simulation. Some important issues surrounding the development of distributed simulation are briefly discussed. A particular attention is focused on the software environment for parallel calculations. The paper describes the system CSA&S/PV (Complex Systems Analysis & Simulation - Parallel Version) which provides framework for simulation experiment performed on parallel machines.

An Algorithm for Control of the Retention Reservoir System Under Uncertainty

Abstract In this paper a system of retention reservoirs is considered. The system is controlled using multiple scenarios uncertainty model. A proposed algorithm considers all future interventions until the end of an assumed horizon. An expected value of a performance index is minimized using a steepest descent algorithm. Constraints on storage and outflows from the reservoirs are also considered. Due to a big number of these constraints, the most difficult problem is connected to the projection of the performance index gradient on active constraints. This projection is performed using a special form of the gradients, so computation effort grows linearly with the horizon length and the number of scenarios.