• Energy Research

This paper presents a new holistic approach that combines solutions for the future power systems. It describes clearly how solar energy is definitely the best outlet for a clean and sustainable planet, either due to their use in both vertical (V) or horizontal (H) forms such as: hydroelectric V&H, wind V&H, thermo-oceanic V&H, water movement sea V&H (tides and waves), solar thermoelectric, PV, and surface geothermal energy. New points of view and simple formulas are suggested to calculate the best characteristic intensity, storage means and frequency for specific places and how to manage the most well-known renewable sources of energy. Future renewables-based power system requires a huge amount of flexibility from different type and size of controllable energy resources. These flexible energy resources can be used in an aggregated manner to provide different ancillary services for the distribution and transmission network. In addition, flexible energy resources and renewable generation can be utilized in different kinds of energy communities and smart cities to benefit all stakeholders and society at the same time with future-proof market structures, new business models and management schemes enabling increased utilization of flexible energy resources. Many of the flexible energy resources and renewable-based generation units are also inverter-interfaced and therefore the authors present future power converter systems for energy sources as well as the latest age of multilevel converters.

This paper reviews the recent studies and works dealing with probabilistic forecasting models and their applications in smart grids. According to these studies, this paper tries to introduce a roadmap towards decision-making under uncertainty in a smart grid environment. In this way, it firstly discusses the common methods employed to predict the distribution of variables. Then, it reviews how the recent literature used these forecasting methods and for which uncertain parameters they wanted to obtain distributions. Unlike the existing reviews, this paper assesses several uncertain parameters for which probabilistic forecasting models have been developed. In the next stage, this paper provides an overview related to scenario generation of uncertain parameters using their distributions and how these scenarios are adopted for optimal decision-making. In this regard, this paper discusses three types of optimization problems aiming to capture uncertainties and reviews the related papers. Finally, we propose some future applications of probabilistic forecasting based on the flexibility challenges of power systems in the near future.

The high penetration of intermittent renewable-based power into modern power systems increases the need for more technical ancillary services from flexible energy resources. Smart homes could provide different flexibility services related to active power control services and therefore fulfill a part of the flexibility needs of system operators. In this regard, the estimation of the flexible capacities of each smart home's flexible device is of key importance. Correspondingly, this paper first estimates the flexible capacities of a smart home with controllable devices as flexible resources. The flexible capacity of each appliance is estimated considering its flexible and non-flexible operations. Besides, the local and system-wide flexibility services are introduced and the paper discusses whether a smart home can provide these types of services. In the simulations of this paper, the flexible capacity of each household appliance is estimated and compared to each other. Finally, the profitability of the smart home's battery energy storage multi-use is analyzed when it is providing three different types of flexibility services for the transmission system operator's needs. The results demonstrate that in some scenarios, the smart home's battery energy storage can increase its profits by providing transmission-system-level flexibility. ; © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) ; This work was supported in part by the FLEXIMAR Project (novel marketplace for energy flexibility) through Business Finland under Grant 6988/31/2018, and in part by the Finnish companies. ; fi=vertaisarvioitu|en=peerReviewed|

There is a need for enhanced flexibility to allow the high penetration of intermittent renewable power into the power system. In this way, transmission system operators (TSO) need more flexible energy resources that help to control the power system frequency by using balancing services. Distribution system operators (DSO) also seek new flexible energy resources that can counteract stochasticity, control voltage level, and manage congestions in distribution networks. Smart homes located in distribution networks are potential resources. Hence, this paper considers a smart home with flexible appliances and devices, including a battery energy storage system (BESS) interfaced with an inverter, an air conditioner (AC), and an electric vehicle (EV). The smart home aims to provide the system operators with coordinated frequency and DSO-level services while respecting the thermal comfort and schedules of the household residence. The inverter-interfaced BESS not only provides active power support for TSO and DSO, but it also injects and consumes reactive power if the DSO needs local flexibility. Fuzzy logic control system is deployed to obtain this goal. In the simulation section, a smart home with flexible appliances is scheduled. Different operations and the economic outcomes are discussed for the smart home considering real-world data. ; © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). ; fi=vertaisarvioitu|en=peerReviewed|

This paper provides a comparison of an energy community energy trading under different regulations and trading structures. In this regard, it considers three cases. In the first case, the community is imposed a fixed price for consuming energy and the community manager aims to maximize the comfort level of its members. In the second case, the community pays for its consumption according to the market prices. The goal of the community manager is to minimize the total costs of the whole community. Finally, regarding the third case, the community trades power based on the negotiated prices with the same goal as the second case. The proposed models are implemented on a hypothetical community with 20 households as a member and the flexibilities of community's flexible energy resources are calculated for each case. ; ©2021 IET. This paper is a postprint of a paper submitted to and accepted for publication in CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library. ; fi=vertaisarvioitu|en=peerReviewed|

During the ongoing evolution of energy systems toward increasingly flexible, resilient, and digitalized distribution systems, many issues need to be developed. In general, a holistic multi-level systemic view is required on the future enabling technologies, control and management methods, operation and planning principles, regulation as well as market and business models. Increasing integration of intermittent renewable generation and electric vehicles, as well as industry electrification during the evolution, requires a huge amount of flexibility services at multiple time scales and from different voltage levels, resources, and sectors. Active use of distribution network-connected flexible energy resources for flexibility services provision through new marketplaces will also be needed. Therefore, increased collaboration between system operators in operation and planning of the future power system will also become essential during the evolution. In addition, use of integrated cyber-secure, resilient, cost-efficient, and advanced communication technologies and solutions will be of key importance. This paper describes a potential three-stage evolution path toward fully flexible, resilient, and digitalized electricity distribution networks. A special focus of this paper is the evolution and development of adaptive control and management methods as well as compatible collaborative market schemes that can enable the improved provision of flexibility services by distribution network-connected flexible energy resources for local (distribution system operator) and system-wide (transmission system operator) needs.

Customers energy consumption pattern affects directly the grid burden, especially during peak hours. In recent years, many different control methods have been proposed to shift the energy consumption to off-peak hours through demand response (DR) management. In order to have effective DR energy management, optimization has a key role. Thus, increasing the benefits for the customers and encouraging them to consider the new controlling approaches in their daily energy consumption pattern is needed for increased customer participation. On the other hand, renewables are integrated with the buildings to decrease the buildings’ energy costs and dependency on the grid utilities. This study moves a step further and considers a few numbers of neighboring houses as an energy community. The community commits to sharing their produced energy from the individual distributed solar system with each other and increasing their energy self-sufficiency by minimizing the import and export of power from/to the grid. This research focuses on applying common electric heat energy storage when community’s own solar PV generation is used to thermal energy generation/storing in heat storage and compares it with the case in which each house has its own distributed thermal energy storage. Then, different sized thermal storages are tested for the community to find the best solution. The results are compared in terms of import and export of energy, annual costs and the payback-time. It is concluded that the community with common thermal energy storage could decrease the energy exchange with the grid and the payback-time of the investments could be reduced for the community members.

Flexibility issues are the main problems arising from the high injection of renewables and distributed energy resources. In order to solve this problem, flexibility potential of distribution-located flexible energy resources should be deployed. In this way, this paper proposes a new local market structure for meeting customer-level flexibility need. In the proposed market structure, the flexibility need of each customer is divided into two parts regarding to the uncertainty coming from forecast errors and variability of the renewable energy sources. In addition, the flexible energy resources are categorized into three types according to the controllability of the flexible resource. Finally, the local flexibility market is settled by matching the flexibility production with the flexibility needs. This is done by considering simultaneously the needed flexibility types with the type of available flexibilities. The local flexibility market is implemented for a hypothetical test system in order to prove the efficiency and liquidity of the proposed market structure.