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Hydro power is one of the most flexible sources of electricity production. Power systems with considerable amounts of flexible hydro power potentially offer easier integration of variable generation, e.g., wind and solar. However, there exist operational constraints to ensure mid-/long-term security of supply while keeping river flows and reservoirs levels within permitted limits. In order to properly assess the effective available hydro power flexibility and its value for storage, a detailed assessment of hydro power is essential. Due to the inherent uncertainty of the weather-dependent hydrological cycle, regulation constraints on the hydro system, and uncertainty of internal load as well as variable generation (wind and solar), this assessment is complex. Hence, it requires proper modeling of all the underlying interactions between hydro power and the power system, with a large share of other variable renewables. A summary of existing experience of wind integration in hydro-dominated power systems clearly points to strict simulation methodologies. Recommendations include requirements for techno-economic models to correctly assess strategies for hydro power and pumped storage dispatch. These models are based not only on seasonal water inflow variations but also on variable generation, and all these are in time horizons from very short term up to multiple years, depending on the studied system. Another important recommendation is to include a geographically detailed description of hydro power systems, rivers' flows, and reservoirs as well as grid topology and congestion.

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Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

Microgrids can be used for securing the supply of power during network outages. Underground cabling of distribution networks is another effective but conventional and expensive alternative to enhance the reliability of the power supply. This paper first presents an analysis method for the determination of microgrid power supply adequacy during islanded operation and, second, presents a comparison method for the overall cost calculation of microgrids versus underground cabling. The microgrid power adequacy during a rather long network outage is required in order to indicate high level of reliability of the supply. The overall cost calculation considers the economic benefits and costs incurred, combined for both the distribution network company and the consumer. Whereas the microgrid setup determines the islanded-operation power adequacy and thus the reliability of the supply, the economic feasibility results from the normal operations and services. The methods are illustrated by two typical, and even critical, case studies in rural distribution networks: an electric-heated detached house and a dairy farm. These case studies show that even in the case of a single consumer, a microgrid option could be more economical than network renovation by underground cabling of a branch in order to increase the reliability.The profitability possibilities of residential microgrids as an aggregator-based solution to the perspective of different stakeholders, for example, utilities, aggregators, and prosumers, were analyzed in [6]. The feasibility and profitability of microgrids participating in the primary frequency control reserve (FCR) market through an aggregator were assessed in [7]. Furthermore, battery energy storage system (BESS) usage on the frequency regulation market was analyzed in [8].According to [9], underground cabling of the network is an effective way for distribution system operators (DSOs) to increase the reliability of power supply. However, underground cabling is expensive.Today, farming is highly automated and electricity-dependent [10], and even short power interruptions are very detrimental. Farming is an energy-intensive industry [11], and thus farmers value the reliability of the electricity supply more so than most of the other customer groups.Farms are located naturally in rural areas, possibly on the long distribution network radial branches with low electricity customer density. The majority of farmers have backup generators (e.g., [11]). Farmers having their own power production to cover a portion of their electricity need is gaining popularity.Several recent studies have focused on microgrid islanded-mode operation, microgrid energy management systems, and power supply adequacy and forecasting (e.g., [12][13][14]). The power supply capability in islanded-mode operation was assessed in [12] over a few hours by using a simulation maximum time step of 1 min. Electro-technical aspects of an unexpected microgrid islanded operation were also analyzed in [14] while considering optimal energy management of...