Stochastic modelling of a hybrid renewable energy system

This paper discusses the issue of modelling a hybrid renewable energy system for a micro-grid connected to a bulk power system. The objective of the work is to create a tool for assessing the feasibility of an energy hybrid system operation with an appropriate control strategy to ensure its efficiency. A hybrid of a solar, a wind and an energy storage device was examined. The integrated model uses statistical indices of solar irradiation and wind speed data to simulate power flow in the system. As the microgrid load demand is variable, power interchange with the bulk power system is managed by a power system supervisor. The control strategy and the load profile of the microgrid must be used to estimate the correct size of the hybrid system storage system. The proposed model was subjected to a case study.В статье рассмотрены вопросы моделирования гибридной электростанции с возобновляемыми источниками энергии для локальной сети, присоединенной к электроэнергетической системе. Целью работы было создание инструмента для обоснования рабочих характеристик гибридных электростанций с выбранными стратегиями регулирования для обеспечения эффективности их применения. Исследована гибридная установка, содержащая солнечную и ветровую электростанции, а также аккумулятор энергии. Поскольку электропотребление в локальной сети изменяется во времени, обмен мощности с электроэнергетической системой контролируется диспетчером. Поэтому, стратегия регулирования и график потребления в локальной сети должны приниматься во внимание для корректного расчета емкости аккумулятора энергии гибридной электростанции. Показано применение разработанной модели на примере конкретной локальной сети.В статті розглянуто питання моделювання гібридної електростанції з відновлюваними джерелами енергії для локальної мережі, що приєднана до електроенергетичної системи. Метою роботи є створення засобу обгрунтування робочих характеристик гібридних електростанцій з вибраними стратегіями регулювання для забезпечення еффективності їхнього застосування. Досліджено гібридну установку, що містить сонячну та вітрову електростанції і акумулятор енергії. Оскільки електроспоживання в локальній мережі змінюється з часом, обмін потужності з електроенергетичною системою контролюється диспетчером. Тому, стратегія регулювання і графік споживання в локальній мережі потрібно враховувати для коректного розрахунку ємності акумулятора енергії гібридної електростанції. Показано застосування розробленої моделі на прикладі конкретної локальної мережі

Agilometer: An Effective Implementation of Internet of Things for Agile Demand Response

Transactive based control mechanism (TCM) needs the IoT environment to fully explore flexibility potential from the end-users to offer to involved actors of the smart energy system. On the other hand, many IoT based energy management systems are already available to a market. This paper presents an ap-proach to connect the current demand-driven (top-down) energy management system (EMS) with a market-driven (bottom-up) demand response program. To this end, this paper considers multi-agent system (MAS) to realize the approach and introduces the concept and standardize design of Agilometer. It is described as an elemental agent of the approach. Proposed by authors Agilometer consists of three different functional blocks, which are formulated as an IoT platform according to the LonWorks standard. Moreover, the paper also performs an evaluation study in order to validate the proposed concept and design

A concept of recipient allowance system for supplier’s failure to maintain the required voltage quality

W artykule przedstawiono propozycję wprowadzenia całkowitego (zagregowanego) wskaźnika, wyznaczanego na podstawie zbioru tradycyjnych miar liczbowych poszczególnych zaburzeń, jako punktowej i systemowej miary liczbowej jakości napięcia. Na jego podstawie wyróżniono trzy klasy jakości: Z, G i NZ. Zdaniem autorów ich wprowadzenie ułatwi analizę porównawczą pomiędzy wyróżnionymi elementami krajowego systemu elektroenergetycznego, tzn. pomiędzy rejonami w ramach jednego operatora, pomiędzy różnymi operatorami oraz pomiędzy oddziałami w ramach sieci operatora przesyłowego. Zaproponowano dwa poziomy regulacji jakości napięcia i system bonifikat: (a) – lokalny, uwzględniający wzajemne oddziaływania dostawcy i odbiorcy energii w punkcie wspólnego przyłączenia, oraz (b) – systemowyThe article presents a proposal to establish an overall (aggregate) indicator determined on the basis of a set of the traditional numerical measures of individual disturbances, as a point and system level numerical measures of voltage quality. The following three quality grades are distinguished on this basis: Z, G and NZ. In the authors’ opinion their establishment would facilitate comparative analysis between featured elements of the national power system, i.e. between regions belonging to a single operator, between various operators, and between divisions within the transmission operator’s grid. The following two levels are proposed for the voltage quality regulation and the allowances system: (a) – local, i.e. taking into account the interaction of electricity suppliers and recipients at the point of common connection and (b) – system

Agilometer: An Effective Implementation of Internet of Things for Agile Demand Response

Transactive based control mechanism (TCM) needs the IoT environment to fully explore flexibility potential from the end-users to offer to involved actors of the smart energy system. On the other hand, many IoT based energy management systems are already available to a market. This paper presents an ap-proach to connect the current demand-driven (top-down) energy management system (EMS) with a market-driven (bottom-up) demand response program. To this end, this paper considers multi-agent system (MAS) to realize the approach and introduces the concept and standardize design of Agilometer. It is described as an elemental agent of the approach. Proposed by authors Agilometer consists of three different functional blocks, which are formulated as an IoT platform according to the LonWorks standard. Moreover, the paper also performs an evaluation study in order to validate the proposed concept and design

Energy Flexometer:an effective implementation of internet of things for market-based demand response in an energy management system

Market-based control mechanism (MCM) needs the IoT environment to fully explore flexibility potential from the end-users to offer to involved actors of the smart energy system. On the other hand, many IoT based energy management systems are already available to a market. This paper presents an approach to connect the current demand-driven (top-down) energy management system (EMS) with a market-driven (bottom-up) demand response program. To this end, this paper considers multi-agent system (MAS) to realize the approach and introduces the concept and standardize design of Energy Flexometer. It is described as an elemental agent of the approach. Proposed by authors Energy Flexometer consists of three different functional blocks, which are formulated as an IoT platform according to the LonWorks standard. Moreover, the paper also performs an evaluation study in order to validate the proposed concept and design.</p

The rise of AGILE demand response: enabler and foundation for change

The distributed resources – distributed generations, storage, electric vehicles and smart appliances – have fueled many disruptions in the conventional grid dynamics. Increasing tough and competitive situations at demand-side have led the stakeholders of power system to reform, because people are more informed and can make decisions that has given rise to turbulent and volatile electricity markets. In such highly diversified and open market environment, the integrated control strategy has expedited the concept of Demand Response. Currently, the important questions in the area of demand response are likely to shift from whether to adopt dynamic pricing to how to achieve fast demand response by the combination of technology and a competitive retail electricity market. This paper assembles the part and parcel in the light of existing technologies for the development of the concept of agility in demand response, that can play a role as a service package which is designed to meet the customer satisfaction efficiently and reliably as well as improve the market responsiveness. For the first time, this paper encompasses the concept of Agile Demand Response that is defined as the ability of power system to survive and prosper in the competitive retail market by reacting to the market needs fast and effectively which are driven by the customers. This paper also presents the key enablers of the agile demand response, which are (1) Retail Market, (2) Virtual Supply-demand matching mechanism, (3) Integrated information system and (4) Stay Committed. The paper concludes that by bringing the enablers together – Agile DR improves the responsiveness to the retail market changes unambiguously

Energy Flexometer: an effective implementation of internet of things for market-based demand response in an energy management system

Market-based control mechanism (MCM) needs the IoT environment to fully explore flexibility potential from the end-users to offer to involved actors of the smart energy system. On the other hand, many IoT based energy management systems are already available to a market. This paper presents an approach to connect the current demand-driven (top-down) energy management system (EMS) with a market-driven (bottom-up) demand response program. To this end, this paper considers multi-agent system (MAS) to realize the approach and introduces the concept and standardize design of Energy Flexometer. It is described as an elemental agent of the approach. Proposed by authors Energy Flexometer consists of three different functional blocks, which are formulated as an IoT platform according to the LonWorks standard. Moreover, the paper also performs an evaluation study in order to validate the proposed concept and design

The evaluation of agile demand response : an applied methodology

This paper formulates an applied methodology for an agile demand response using mathematical micromodels. The optimal strategy chosen by an aggregator is the maximization of social welfare derived from demand flexibility. The notion of complex demand bidding is already given in the litera-ture, however heretofore it is formulated as the relationship of price with both demand elasticity and marginal cost along with temporal and profit constraints. Although the planning of flexible demand is already handled by using advance learning techniques in literature, herein simple Q-learning technique in a decentralized fashion is proposed. Moreover, trade-offs between the proposed complex bidding rules are explored in a day-ahead market context. Due to the given complex bidding rules and principle of learning, the methodology can be easily applied in active distribution network. Several number of houses, equipped with the proposed complex bidding mechanism and decentralized learning capability, has been simulated, thus illustrating the application of methodology formulated herein