Weronika Radziszewska

Intelligent Computations in an Agent-Based Prosumer-Type Electric Microgrid Control System

The growing number of small prosumers, progress in construction of the renewable energy sources and opening of the energy markets lead to development of the concept of a microgrid. To increase efficiency of electricity consumption, production, and trading, energy managing systems (EMS) are being developed. In this paper we present a project of a complex EMS that will combine load scheduling, power balancing and smart trading methods to optimize electric energy costs of running a simulated research and education center. We present a concept of a distributed Agent-based Power Balancing System that controls the power flow in a microgrid by decentralized and distributed decision making. The program optimizes the operating (exploitation) cost of the devices in the microgrid by internally balancing, as much as possible, the produced and consumed power and by trading the remaining energy excesses or deficits on the external market. Agents associated with the devices cooperate using communication protocols. Their aim is to use the energy from renewable energy sources whenever it is only available, and at the same time limit use of the energy from the sources that are more expensive and less environment friendly.

Dynamic Pricing and Balancing Mechanism for a Microgrid Electricity Market

The trading is a well known, easy and efficient method of distributing goods. Energy cannot be stored efficiently, which implies that supply and demand of power has to be balanced at all times; this adds complexity to the trading of electric power. Introduction of microgrids, with internal balancing of power and trading with external power grid, brings many questions about power distribution, sharing of costs and revenues. Using market mechanism for such purpose seems appropriate. In this article we present an example of balancing a microgrid with its own energy production sources and connected to a higher voltage distribution grid, by introduction of the continuous double auction market with agents following the Adaptive-Aggressive Strategy.

Integration between Web Services and Multi-Agent Systems with Applications for Multi-commodity Markets

This chapter analyzes possibilities of integration between Web services and multi-agent technology. Efforts of Agents and Web Services Interoperability Working Group (AWSI WG) are described, which is focused on Web Services and FIPA (Foundation for Intelligent Physical Agents) interoperability. A hybrid architecture for conducting trade in a multi-commodity markets, which is based on multi-agent approach combined with the best practices and standards of the Service Oriented Architecture is also proposed. The architecture allows the trade to be conducted by large parties with well structured and defined offer as well as smaller entities, which operate on smaller scale and do not have resources to build full featured catalogues.

El Farol Bar problem, Potluck problem and electric energy balancing - on the importance of communication

Power balancing is an important issue when micro-grids in island mode are considered. It requires active, real-time decision making to minimise the imbalances. El Farol Bar and Potluck problems are artificial problems designed to challenge the decision making process in a situation of limited information. They are theoretical, ill-defined problems designed to show that rational decision making in a situation of scarce information can give worse results than non-rational behavior. Potluck problem can be compared to electric power balancing in microgrids. But due to reduced complexity and constraints of theoretical problems and differences in goal functions the approach has to be in each case different. The study of these differences in this paper shows the importance of exchange of information between participants (or agents); it also suggest what type of information are necessary in what conditions. The amount of information that needs to be exchanged depends on the relation between participants (agents): the less cooperating their relation is, the less information they are willing to exchange.

A Multiagent Energy Management System for a Small Microgrid Equipped with Power Sources and Energy Storage Units

An Energy Management System (EMS) for a small microgrid is presented, with both demand and production side management. The microgrid is equipped with renewable and controllable power sources (like a micro gas turbine), energy storage units (batteries and flywheels). Energy load is partially scheduled to avoid extreme peaks of power demand and to possibly match forecasted energy supply from the renewable power sources. To balance the energy in the network on line, a multiagent system is used. Intelligent agents of each device are proactively acting towards balancing the energy in the network, and at the same time optimizing the cost of operation of the whole system. A semi-market mechanism is used to match a demand and a production of the energy. Simulations show that the time of reaching a balanced state does not exceed 1 s, which is fast enough to let execute proper balancing actions, e.g. change an operating point of a controllable energy source. Simulators of sources and consumption devices were implemented in order to carry out exhaustive tests.

Equilibria in Concave Non-cooperative Games and Their Applications in Smart Energy Allocation

Game theory is often applied to modeling interactions of non-cooperative decision makers. Such interaction appear, among others, in the case of energy management. In this context we formulate the problem of energy allocation for a group of electric vehicles in a smart grid. Subsequently, we formulate a game-theoretic model of interactions of agents controlling vehicle charging schedules. An algorithm for computing pure Nash equilibrium in such game is presented. Moreover, we introduce a solver, which is specifically designed to find equilibria in concave games. The core of the proposed solver is based on the primal-dual interior-point method for nonlinear programming. Experimental results of applying the solver are compared with a centralized solution.

Application of an Auction Algorithm in an Agent-Based Power Balancing System

The paper presents an application of an auction algorithm in a computer multi-agent system for managing the unbalanced energy in a microgrid. The main goal of the system is to control and minimize the differences between the current energy demand and the actual energy production, using an auction algorithm. The assumption of distributed generations in the microgrid, which includes renewable power sources, is made. The storages, and the controllable power sources improve the system operation. The differences between the actual demand and generated energy are caused by unpredictable level of electric power generation by uncontrolled sources (mainly wind turbines and solar panels) and/or randomness of power utilization. The system will tend to balance these differences on-line in short time intervals (about one minute) to follow-up the varying level of local power generation and loads.

Control Charts Designed Using Model Averaging Approach for Phase Change Detection in Bipolar Disorder

Bipolar disorder is a mental illness affecting over 1% of the world’s population. In the course of disease there are episodic fluctuations between different mood phases, ranging from depression to manic episodes and mixed states. Early detection and treatment of prodromal symptoms of affective episode recurrence is crucial since it reduces the conversion rates to full-blown illness and decreases the symptoms severity. This can be achieved by monitoring the mood stability with the use of data collected from patients’ smartphones. We provide an illustrative example of the application of control charts to early and reliably generate notifications about the change of the bipolarity phase. Our charts are designed with the weighted model averaging approaches WAM* and WAMs for the detection of disturbances in the stability of the monitored processes. The models are selected in a novel way using the autocorrelation functions. The proposed approach delivers results that have clear, psychiatric interpretation. Control charts based on weighted model averaging are a promising tool for monitoring patients suffering from bipolar disorder, especially in case of limited amount of diagnostic data.

Optimal Parameter Ranges in Fuzzy Inference Systems, Applied to Spatial Data

Processing of spatial data can benefit from the use of fuzzy inference systems, and such systems have been proposed to deal with the map overlay problem for gridded data. The development of fuzzy inference system for solving spatial problems poses specific challenges due to the type of data and specific properties of the spatial context. In this contribution, we take into account that a spatial dataset can exhibit a big variety in different areas and determine the most possible ranges for the variables in the rulebase system in a more appropriate and dynamic way. In addition, we show how the construction and application of a rulebase can be modified in order to handle this changed definition of the most possible ranges.

Spatial Data Analysis in Archaeology: Computer-Aided Selection of Priority Location for Archaeological Survey

The article describes a method to help experts selecting the most probable locations of settlements inhabited by the people in Crete under the Venetian rule (1204–1669). The method ranks the possible location in the designated area based on a set of criteria, but also considering the natural obstacles, e.g. terrain. This multi-criteria task is solved using a modification of the Bellman-Ford algorithm for each criteria and then combining them using weighted sum. The explanation is supported by a small test case.