Electrical Grids with High Penetration of RES

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Electrical Grids with High Penetration of RES

As discussed in section I.1, the massive penetration of RES into the electricity grid is already tangible in the European electricity mix and it has turned into a cause of concern for different European grid operators. Despite their potential environmental and economic benefits, large-scale integration of RES leads to new technical and regulatory issues in order to ensure a reliable and economical operation of the entire electrical system.
Often the variability, intermittency, and unpredictability of solar-driven resources, such as wind and irradiation have posed as constraints and decelerated the massive RES diffusion.
However, their widespread availability and low energetic density, combined with the numerous economic incentives, have induced a diffusion throughout the sector of small and medium-sized RES. Consequently, a new term was coined to describe this new situation: Distributed Generation (DG).
Currently, no unique definition on how a DG should be exists in literature. However, researchers and industries have agreed on basic characteristics of DGs. They are small-sized power generators or storage systems, which typically range from a few kW to tens of MW, and they are not part of a larger power system [13]. Moreover, they are typically installed close to the consumption and they can be operated connected or isolated from the main grid [13]. The CIGRE working group stated some robust and representative characteristics in order to classify a power system as a DG. In general, the power of a DG must be smaller than 10–50 MW [13].
Furthermore, due to their size they are usually connected to the distribution network and they are not planned or dispatched in a centralized way [13].
In fact, in Europe, more than 90% of solar and wind systems are connected to distribution grids [14]. Moreover, if analysis focuses especially on photovoltaic plants, this percentage is even higher. The Italian case could be taken as an example. In 2014, the number of installed photovoltaic plants accounted to 648,418, corresponding to a total power of 18.6 GW [12].
Furthermore, analysing in detail the statistics diffused by the Gestore Sevizi Energetici revealed that the PV systems with a power greater than 5 MW correspond around 0.03% of the total number PV systems installed which represents 9.7 % of the total installed power. On the contrary, systems with an installed power lower than 1 MW represent 99.8 % of the total number PV systems installed and constitute 77.8% of the total national installed power. Pie charts in Fig. I.9 and Fig. I.10 promptly show these statistics on both installed capacity and number of PV systems.
This large diffusion of small DG already places distribution system operators (DSO) at the core of the energy transition. Until now, DSOs have had the obligation to assure the grid access to RES-based DGs and also to absorb all the produced energy by RES (except in emergency cases) [15]. Hence, DSOs today are confronted by new tasks and roles. In fact traditionally, the role of distribution was to locally distribute electricity in order to feed small and medium sized consumers through medium and low voltage networks. Medium and low voltage networks have traditionally been passive with unidirectional energy flux, leaving the TSOs the role to ensure energy balance between consumption and production. This distributed electricity was centrally produced by large-sized conventional systems, such as nuclear and coal power plants, and supplied by high voltage lines to distribution grids.
In theory, due to their proximal location to consumption, DG should positively contribute to an efficient system management. DG may reduce transmission and distribution power losses by limiting long-distance transport, help to improve power quality and security of supply, reduce grid investments by decreasing peak load and congestions, and so on. However, in practice, renewable-based DGs induce various negative impacts on distribution grids operation, such as feeders’ voltage variation, issues in protection and automation systems, increase in short circuit currents, undesired islanding, etc.
In general, DGs confer an extremely heterogeneous architecture to distribution grids, due to their variability in type, size and location. Distribution grids are not passive anymore and are becoming bidirectional in terms of energy fluxes. Voltage variation is one of the most important impacts to be considered. DGs induce voltage profile variation in the supplied feeder, which no longer represents a linear descending line from the substation until the last supply point. Furthermore, this voltage variation can also be significant with respect to the point of power injection by DG as it could accelerate insulation damage in network components as well as exceed permissible technical standard limits.
In one of the first reviews on DG impacts, authors discussed a reasonable rule-of-thumb according to which shared feeders among DG and consumption in secondary level, even a small generator that injects about the 5% of current at the primary level could cause a voltage regulation risk to customers sharing the feeder [16]. Briefly, majority of the medium voltage radial grids are mainly regulated by using an on-load-tap-changer in the substation transformer, which responds to current variations and is able to increase/decrease the secondary voltage with steps of 1.5% of the rated nominal voltage and within a range of ±15% of the rated nominal voltage. The heterogeneous architecture does not assure the performance of this strategy. Cable reinforcement through wider cables could also be seen as the solution for voltage issues [17]. However in order to increase the utilization rate of grids, this centralized solution needs to be combined with local actions.
Another factor to be considered is that DGs are only partially dispatchable. This is mainly due to their variability and stochastic intermittence. Hence, although they are closer then power sources connected to the high voltage networks, they are not always located in close proximity to the elements that are consuming and often their production does not coincide with the local power demand. For example, the power peak of small and medium size of residential and commercial users occurs in the late afternoon hours when PV is not available or is simply at the end of its daily production cycle. The asynchronisation between load and generation, combined with their non-dispatchability, makes DGs hardly useful for constrained grids support and congestions might also occurs. Hence, the need to oversize the distribution grids for peak load remains and the capital expenditure for grid reinforcement also rapidly increases in case of densely populated feeders of DGs. Reinforcements and expansion of distribution grids in order to increase the hosting capacity of RES requires huge investment costs and extensive planning analysis.
Germany is undergoing a massive RES integration and the level of investment has risen in recent years and is estimated to continue to grow in the future [14]. As divulged by the Federal Network Agency in October 2016, Fig. I.11 shows the investments made in Germany for new constructions, expansions and maintenance for both transmission and distribution networks. In 2015, around 3.8 billion € 2 were invested for the expansion of distribution grids [14]. The increase in CAPEX may induce higher connection costs for DG’s owners [17] and/or higher grid tariff for passive3 users [14]. In general throughout Europe, the investment needs for the distribution sector will be much higher than for transmission grid and represents around 80% for the German case [8], as also observed in Fig. I.11.
The large-scale integration of RES into distribution grids is not the unique issue related to power system modernization. In recent years, RES subsidies, such as Feed-in Tariffs and quota obligations mainly based on Green Certificate, have been key support mechanisms to help foster RES and integrate them into the electricity system. Feed-in Tariff schemes acted as economic incentives to RES producers and were independent of the electricity market price fixing mechanism. New schemes, such as Feed-in Premiums, have also been introduced in order to test the introduction of high and medium sized RES in the electricity market. In fact, in the long term, large scale renewable-based plants have to be integrated into the electricity market, while maintaining an economically competitive structure. However, what will happen if the amount of energy produced by small and medium sized generators reaches a high value? Hence, solutions for market access (forward or wholesale) of these systems are discussed in the literature, e.g. in MASSIG Project [18].
In general, the integration process of intermittent, variable and partially dispatchable sources into the power system will first and foremost require the exploitation and development of new active strategies which exploit flexible elements, such as energy storage and demand-response. The revision and evolution of current regulations have to be carried out as well and the two solutions have to go hand in hand in order to ensure technical as well as economical robustness of the future electrical system.
Storage systems can facilitate the access of renewables into market and grid applications by addressing the uncertainty of availability of resources and providing capability to supply the contracted scheduled power and/or energy. Moreover, they can also mitigate the aforementioned asynchronisation between consumption and production. Both stationary energy storage systems (ESS), such as stationary batteries or fly-wheels, and mobile systems, such as electrical vehicles, are expected to play an important role in this energy transition. Currently in the overall European electricity system, only around 5 % of the installed production capacity is installed as storage capacity and the storage park is mainly composed of pumped hydroelectric energy storage [8]. The required storage capacity will change based on different scenarios of RES mix in the total production capacity. However, a range between 43 GW and 90 GW of storage capacity is expected to be introduced for European scenarios by 2050 with estimated investments between 80 Billion $ and 130 Billion $ [8].
For stationary applications, various systems are available in the current market. All these technologies have different characteristics and performances, costs, specific power and energy, maximal capacity, energy density, efficiency, lifetime, and so on. Electrochemical systems are considered to be the most interesting technology for small and large scale applications in the electrical system. In fact, they have high specific power and energy, high efficiency and they are modular, which allows a flexible use. Moreover, they have much shorter installation periods when compared to hydroelectric pumping stations, and they can be installed almost everywhere and especially in close proximity to many connection points of renewable power plants. Li-ion technology is the most promising technology among the various electrochemical systems, thanks to their performances. In the next few years, their large integration will depend on their economic competitiveness. The Li-ion based battery costs is expected to drastically decrease. Since 2007, it started to fall by about 14% each year [19]. Already by 2014, Li-ion pack costs were below the average projected costs for the year 2020 [19]. Authors in [19], projected optimistic and pessimistic scenarios in Li-ion costs trend for electrical vehicle applications by analysing data from multiple sources available in the literature. According to these scenario, the average cost will be between 150 $/kWh and 250 $/kWh in 2025.
The second core element of flexibility in this energy transition is the consumption. Traditionally, the consumption has been almost entirely considered inelastic. However in recent years, smart use of power demand is considered a helpful and efficient program to manage RES variability and intermittence. Hence, in the literature several studies are proposed. In Scotland, authors affirmed that the available demand capacity for power flexibility is around 5% of the global available demand for the evaluated scenario (1700 MW peak) [20]. Furthermore, up to 15% of the rated fan power of a HVAC system may be employed for grid services, without impacting the occupants’ comfort [21]. More detailed studies have shown that the available flexibility can also be more than 15% if used for a limited timeframe. For example, results indicated that a reduction between 30% up to 60% in the air-supplied fan power could be applied for around 120 min without compromising indoor air quality [22]. In practice, the use of flexibility offered by power demand response has started to be reinforced into current regulations. For example in France through the new TURPE, new mechanisms were actuated in August 2017 in order to reinforce the temporal economic signals which aim to influence and control the consumption peaks. The first new mechanism, the mobile tariff option on the HV network (20 kV), would encourage erasure of load during national peak load periods.
The combined use of distributed generators with these flexible systems by implementing advanced management and control functionalities is nonetheless a required capability in order to guarantee a reliable and economic integration of these multi-technology systems into the power system and in order to implement active management strategies for its operation. A promising way to implement these management and control capabilities on a national scale lies on a coordinated and systematic approach of sub-systems, known as the microgrid concept [15].


Research Approach and Thesis Contributions

This thesis draws its inspiration from the energy transition movement and its evolution context, one where electrical grids will be soon populated by numerous small and medium sized distributed sources.
In particular, this work is driven by many questions still open to be explored, such as:
 Can the functional architecture of microgrids guarantee interoperability among various technologies? And how?
 Can users respect their self-interests and privacy and at the same time work in a collaborative way?
 Can a microgrid be seen as a coherent and controllable structure from the exterior?
 Are microgrids flexible and controllable elements?
 Can several microgrids collaborate by respecting their willingness to participate and different technical behaviours?
 How does microgrid react in real-time when participating in electricity or service markets?
 Can microgrids contribute to a smart and active management of grids?
 Which basic information are required to be shared?
 …
Hence, this thesis aims to conceptualize, develop and implement new management strategies for electrical grids in order to facilitate the high penetration of RES. The massive

Table of contents :

I.1. Energy Scenarios: Opportunities and Challenges
I.2. Electrical Grids with High Penetration of RES
I.3. Research Approach and Thesis Contributions
I.4. Thesis Contents and Organization
II.1. Introduction
II.2. Microgrids: The backbone of Smart Grids
II.2.1. Concept and Characteristics
II.2.2. Operation and Control
II.3. Multi-Microgrid Systems
II.4. Aggregator position and needs
II.5. Agents and Multi Agent System
II.5.1. Agent and intelligent agent concept
II.5.2. Multi-Agent System benefits for Smart Grids
II.5.3. MAS implementation
II.5.4. MAS development with JADE for Smart Grid
II.6. Conclusions
III.1. Introduction
III.2. Energy Management of Microgrids
III.2.1. Objectives and Phases
III.2.2. Management Architecture Description
III.3. Rule-Based Approach for Day-Ahead Scheduling
III.3.1. Logic Rules for Rule-Based Microgrid Scheduling
III.3.2. Case Study
III.4. Optimization-based Approach for Day-Ahead Scheduling of Microgrids
III.4.1. Single-Objective Optimization Problems
III.4.2. Mathematical Formulation for Optimization-Based Microgrid Scheduling 75
III.4.3. Case Study
III.4.4. Sensitivity Analysis
III.5. Comparison between Rule-Based and Optimization-based Approaches
III.6. Conclusions
IV.1. Introduction
IV.2. Multi-Objective and Multi-Level Programming
IV.3. Architecture and Sliding Multi-Level Optimization for Multi-Microgrid Scheduling
IV.3.1. Sliding Multi-Level Optimization using MAS
IV.3.2. Aggregator model: Cost and Revenues Allocation
IV.4. Multi-Microgrid Scheduling for Active Congestion Management and Market Participation
IV.4.1. Active Congestion Management Methods
IV.4.2. Flexibility Service Market
IV.4.3. Capacity Limit Allocation
IV.5. Centralized
IV.6. Conclusions
V.1. Introduction
V.2. Rolling Optimization-based and Rule-based Approach for Intra-Day and Real-Time Control of Microgrids
V.2.1. Real-Time Control Layer
V.2.2. PV and Load Forecast Layer
V.2.3. Intra-Day Optimization Layer
V.3. Description of the Implemented Experimental Test Bench
V.4. Scenarios and Test Results
V.4.1. Scenario 1 – Good PV Forecast
V.4.2. Scenario 2 – Forecasted PV Power higher than the measured one
V.4.3. Scenario 3 – Forecasted PV Power lower than the measured one
V.4.4. Scenario 4 – Forecasted PV Power Lower than measured one with High Intermittence
V.5. Conclusions
VI.1. General Conclusions
VI.2. Outlook on future research
Appendix A
Appendix B
Appendix C


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