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CHALLENGES AND OPPORTUNITIES OF RENEWABLE ENERGY SOURCES IN LOCAL ENERGY COMMUNITIES
Introduction
The capacity deployment of distributed energy resources (DERs) is showing its increasing trend with more and more integration of distributed generators (DGs). As a result, energy communities have emerged with individual community energy requirement [2].
In the coming decades, traditional centralized electricity supply structure is greatly challenged as the households/communities are transformed gradually from electrical ‘passive consumers’ to ‘prosumers’ (producer + consumer) and finally to active “prosumers” providing also ancillary services for the technical management of the electrical network. With the rapid increase of renewable energy technologies applications, communities have been involved in electricity provision and energy projects in many countries. There are diverse motivations, including environmental profits for more sustainable and renewable energy [3]; economic profits with social and technological innovations, e.g. more options for customer-oriented autonomous energy management, more flexible electricity tariffs, or concerns about social equity problems [4].
Under this context, the challenges and opportunities arising from these motivations should be focused and addressed. First, this chapter presents a current state of the art regarding the development of RES and local energy communities. Then, backgrounds on energy management systems are introduced with a review of research activities on this topic at the laboratory. Fundamentals on generation scheduling in an energy system are recalled then bibliographic reviews are given on employed deterministic optimization techniques. The problem of uncertainties is introduced and stochastic optimization techniques are reviewed. Hence, a synthesis of relevant information paves the scientific roadmap, that is developed in next chapters.
Renewable Energy Sources
Context and motivations
Electricity generation keeps rising in recent decades, satisfying a growing energy need in worldwide. According to IEA (International Energy Agency), global electricity demand has grown by 4% in 2018 to more than 23 000 TWh, contributing to a growth of 20% in total final consumption of energy [5]. Currently, fossil fuels, like coal, natural gas and oil, are the main sources of world electricity generation.
However, fossil fuel consumption leads to potential energy crisis in the future. With the limited non-renewable sources, more sustainable approaches are required. Furthermore, fossil fuels bring greenhouse gas (GHG) emissions, which contribute to the global warming. An IPCC (Intergovernmental Panel on Climate Change) special report showed the impacts of global warming of 1.5 °C on natural and human systems, and analyzed the threat of climate change [6].
To address these problems, many countries and regions have taken strong initiatives to increase their energy efficiency and renewable energy capacity. There has been a large increase in international agreements and national energy action plans. In March 2007, the European Union (EU) leaders have set so-called “20-20-20 targets” for the year 2020, aiming to a reduction of GHG emissions by 20% from 1990 levels, an increase of renewable energy’s market share to 20%, and a 20% increase in energy efficiency. On the basis of 2020 targets, the “2030 climate and energy targets” were adopted by the European Council in October 2014, and were revised upwards in 2018. The targets for 2030 are [1]:
• Reduction of GHG emissions by 40% compared with 1990 levels,
• Increase of renewable energy by 32%,
• Improvement in energy efficiency by 32.5%.
In December 2015, the Paris Agreement sets a goal to limit the increase in global average temperature to well below 2°C above pre-industrial levels, and to attempt to limit the increase to 1.5°C. Implicit in these goals is the need for a low-carbon energy sector. All these targets and international agreements are decided to ensure the decarbonization in European energy system with net-zero GHG emissions by 2050.
Trigged by these demands and motivations, renewable energy sources (RES) are promoted to make more reliable, cost-effective, and environmental-friendly energy generation. The growth of RES, like hydropower, wind, solar, geothermal, biopower, has accelerated in the last decade. According to the International Renewable Energy Agency (IRENA), during 2009-2018, the renewable energy capacity has been doubled, with 1221 gigawatts (GW) of renewable energy added to the global electric power system [7]. The share of renewables in total generation capacity has increased from 22% to 33% over the period 2001-2018. In terms of the growth rate, a long-term growth in renewable generation capacity and its contribution to the global energy transition is given in Fig. 1-1. The share of renewables in the growth of electricity generation capacity (percentage of renewables in net capacity growth) has increased from about 25% in 2001, passing 50% in 2012 to reach 63% in 2018. On the contrary, as the figure shows, the expansion of non-renewable generation capacity has shown a slight sign of slowing down.
The EU has made efforts to achieve the 2020 target of increasing share of renewable energy as well as reducing the GHG emissions. Fig. 1-3 shows the increasing trend of renewable energy in EU, reaching around 18% in 2018. However, the objective of 20% is not expected to be reached in 2020 with the current increasing rate.
In terms of GHG emissions in Fig. 1-4, the target has already been reached in 2013 with 20% of reduction in EU compared with 1990 levels. Whereas, the reduction rate becomes showing a stable, even a slight fluctuate trend since 2014. This implies that related measures and incentives that implemented were not enough to close the gap to the 2020 goal. Similar trends can be observed in France regarding GHG emissions and the integration of renewable generation. Especially GHG emissions are far from attaining the goal of reduction. Overall, despite that the impressive growth of renewables, the transition to low-carbon European energy system will require more efforts not only on expanding renewable capacity, but also on retiring or converting more of their existing fossil fuel power plants.
Renewables in power systems: challenges
The electricity sector is experiencing its most drastic transformation since its creation, more than a century ago. Electricity is increasingly relying more on lighter industrial sectors, services and digital technologies. Its share in global final consumption is approaching 20% and is set to rise further. Policy support and technology cost reductions are leading to a rapid growth in variable renewable sources for electricity generation. Emissions reduction efforts are thus made by power sectors. Whereas, the entire system relating energy and electricity is required to operate differently from the
Affordability, reliability and sustainability are closely interlinked in power systems. Each of them, and the trade-offs between them, require a comprehensive approach to energy policy. For example, wind and solar photovoltaics (PV) bring a major source of affordable, low-emissions electricity, but create additional requirements for the reliable operation of power systems. Furthermore, managing potential shortfalls in supply is a must for suppliers of interconnected global market [10]. The challenges of integrations of RES in power systems are summarized as follows.
Firstly, the installations of some RESs are limited by geographic and meteorological factors. For instance, the PV capacity is largely dependent on hours of daylight and illumination intensity of the region. Hydropower and biomass require large spaces for the natural resources’ storage. Hence RESs should be implemented with the consideration of nature limits.
Secondly, RESs, e.g. solar and wind, are highly intermittent and partially unpredictable, inducing reliability issues on the electrical power production. The amount of power that solar and wind can produce depends on the availability of the sun and wind. As the sun radiation and wind speed are never constant, therefore the output power of a solar energy system or a wind power varies during the day. Because they are highly influenced by weather conditions, RESs bring some unpredictable generation uncertainties and risks to an on-going unbalancing between power generation and power consumption in electrical grids to enable an instantaneous power compensation. Hence, high penetration of RESs can result in risk of making the entire power system less reliable. The stochastic behavior of RESs leads to an increasing demand for flexibility in electrical grids. More flexible technologies of generation, consumption or energy storage should be developed to maintain the electricity stability.
Thirdly, power quality problems occur with a high penetration level of RESs. Power quality of a power system depends on voltage variations (over-voltage and under-voltage), frequency variations and harmonics [11]. Voltage fluctuations are especially challenging when RESs are participating. For example, when the PV power is injected into the electric system, or a large wind turbine is stopped, the voltage fluctuation may beyond the acceptable range. Hence the RESs-based distributed generation (DG) plant should be carefully designed to maintain the quality of the voltage in distribution and transmission networks [12]. For example, advanced PV inverters are needed for long-term dynamic stability and voltage regulation.
Opportunities for a better integration of renewable energy sources
For a better integration of distributed RESs, opportunities exist for at least three stakeholders: the energy source, the electrical network, and the consumer [13].
Energy source opportunities
The costs of solar PV, wind and battery storage showed its tendency to decline continuously. According to IEA, costs of new solar PV have decreased by 70%, wind by 25% and battery costs by 40% since 2010 [10]. In 2016, growth in solar PV capacity was larger than for any other form of generation. The fast deployment of solar photovoltaics (PV), led by China and India, is expected to help solar become the largest source of low-carbon capacity by 2040. At that time, the share of all renewables in total power generation is expected to reach 40%. In the European Union, renewables account for 80% of additional generation capacity. Wind power will become the leading source of electricity soon after 2030, due to the strong growth of both onshore and offshore projects.
The rise of uncontrolled power generation from solar PV and wind power requires more additional power balancing capacities for compensation and so gives great importance to the flexible operation of power systems in order to guarantee the electrical grid security. Today, conventional power plants are still the main sources of system flexibility and ancillary services (ASs). However, new flexible technologies are developed, such as centralized storage systems, hybridized storage with intermittent renewable energy generators, demand-side response with controllable loads and new interconnections for bidirectional power exchanges. These technologies need to be further developed and well-integrated in order to provide more flexibility and controllability of the power balancing in a more economic and environmental-friendly way.
Electrical network opportunities
The European Union makes efforts to achieve an “Energy Union” through the emergences of new local electrical network architectures, e.g. smart grids and microgrids, which improve energy efficiency and security. With the distributed connection of many low power RESs, more and more energy systems and energy communities are developed with a decentralized structure. Those decentralized grids are operating to create a more reliable, more sustainable and more resilient electrical energy infrastructure. Smart cities, smart grids and microgrids are always favored because of their advantages regarding generation, transmission, distribution, operation and management technologies (e.g. communication networks). These smart networks bring flexibilities for transmission and distribution thanks to their decentralized structures. Moreover, with the regulation of distributed system operators, smart networks offer opportunities for a better cooperation with varying DGs.
To manage their electrical networks and satisfy technical constraints, distribution system operators consider more and more advanced storage devices and control strategies in order to control the RMS value of AC voltages, limit currents under rated values of lines and cables or provide ancillary services (ASs) [14]. Long-time or short-time fluctuations can be handled with the help of energy storage systems, so that dynamic power productions from RESs are more easily integrated into the networks.
Thanks to the lower costs of implementations, battery energy systems have been assessed to manage dynamic fluctuations of powers [15].
Consumer level opportunities
With increased RESs participation, the definition of ‘prosumers’ has emerged, referring to ‘energy user who generates renewable energy in its domestic environment, then either stores the surplus energy for future use or sells to the interested energy buyers’ [16]. It is crucial to coordinate prosumers to perform a sustainable and reliable sharing procedure of the local produced electricity to develop smart grids, smart energy systems and smart energy communities. For example, developed technologies of electric vehicles (EVs) and energy storage systems bring energy flexibility between consumers and producers with their conversion ability. Moreover, demand-side response enables the use of electricity more intelligently according to adequately with production, distribution and transmission constraints. As examples, rather than simply generating more electricity to meet short periods of huge demand, hotels might turn down their air conditioners for a while, or large factories might delay an energy-intensive process to another time, in order to reduce peak demands on the energy grid.
Under this context, these opportunities with regard to energy sources, electrical network and consumers, should be definitely considered when envisaging a better integration of distributed RESs in an electrical network. An advanced smart grid/microgrid structure should be developed with more intelligent energy management system (EMS) technologies for flexible power for energy transfers as energy storage system (ESS). In addition, up-to-date operation and management technologies, e.g. operational planning methods under RESs uncertainties, or energy storage control strategies for ancillary services provision, should be also properly implemented.
Energy Management in Local Energy Communities
Emergence of energy communities and evolutions
Historically, to reduce investment costs, electric power systems have been built and rely on large central power plants, sending electricity through long distance transmission lines to residential or industrial destinations where electricity is actually needed. The meshed architecture of transmission networks has also demonstrated their interest for rerouting power flows in case of faults. The emergence of distributed generation (DG) shows its advantages and prospects in energy communities due to environmental-friendly characteristics and better power system efficiency since the electricity is locally produced and consumed, avoiding losses from transport and distribution of electricity. DG offers opportunities to relief existing pressures on assets and operations for transmission and distribution systems by offering local energy provision possibilities [17]. The integration of DERs in energy communities is based on renewable energy sources (RES) and micro-sources, e.g. photovoltaic (PV) system, wind turbine, internal combustion engines, fuel cells, gas turbines, microturbine using combined heat power (CHP) system, electric vehicles, and controllable energy storage devices, etc [18].
Under these circumstances, the concept of ‘prosumer-community’ is defined in [19] as an approach to manage and interconnect prosumers in the form of goal-oriented virtual communities. Hence organizing and managing prosumers to develop a sustainable and reliable energy-sharing process has become crucial to smart grids, energy systems and energy communities.
Table of contents :
ACKNOWLEDGEMENTS
CONTENT
LIST OF FIGURES
LIST OF TABLES
LIST OF ACRONYMS AND VARIABLES
GENERAL INTRODUCTION
CHAPTER 1 CHALLENGES AND OPPORTUNITIES OF RENEWABLE ENERGY SOURCES IN LOCAL ENERGY COMMUNITIES
1.1 INTRODUCTION
1.2 RENEWABLE ENERGY SOURCES
1.2.1 Context and motivations
1.2.2 Renewables in power systems: challenges
1.2.3 Opportunities for a better integration of renewable energy sources
1.3 ENERGY MANAGEMENT IN LOCAL ENERGY COMMUNITIES
1.3.1 Emergence of energy communities and evolutions
1.3.2 A decentralized energy community case: Local Community Microgrids
1.3.3 Integration of RESs, energy storage and hybrid active generators
1.3.4 Energy management system
1.3.5 Experiences in central energy management at L2EP
1.4 GENERATION SCHEDULING
1.4.1 State of art: Unit Commitment and Generation Scheduling
1.4.2 Deterministic optimization
1.4.3 Forecasting of RES and Uncertainties Handling
1.4.4 Integration of probabilistic approaches in DUC
1.4.5 Stochastic optimization
1.5 CONCLUSION
CHAPTER 2 UNCERTAINTY ANALYSIS FROM FORECASTING
2.1 INTRODUCTION
2.2 UNCERTAINTIES IN POWER SYSTEM
2.2.1 Sources of uncertainties
2.2.2 Solar generation uncertainty
2.2.3 Load demand uncertainty
2.3 FORECASTING OF PV GENERATION AND LOAD DEMAND
2.3.1 Fundamentals and context
2.3.2 BPNN application for PV production forecasting
2.3.3 BPNN application for load forecasting
2.4 UNCERTAINTY ANALYSIS IN GENERATION SCHEDULING
2.4.1 Introduction
2.4.2 Uncertainty characterization with distribution functions
2.4.3 Uncertainty representation in stochastic optimization
2.4.4 Uncertainty propagation
2.4.5 Sensitivity analysis
2.5 CONCLUSION
CHAPTER 3 DETERMINISTIC UNIT COMMITMENT UNDER UNCERTAINTY
3.1 INTRODUCTION
3.2 STATE OF ART OF DUC WITH OR AND RESEARCH TASKS
3.2.1 DUC under uncertainty
3.2.2 Synthesis
3.3 DEALING WITH UNCERTAINTY: POWER RESERVE
3.3.1 Introduction
3.3.2 Frequency control reserve types
3.3.3 Deterministic criterion for OR sizing
3.3.4 Probabilistic criterion with consideration of RESs uncertainties
3.4 RESERVE QUANTIFICATION WITH A RISK-CONSTRAINED PROBABILISTIC METHOD
3.4.1 Analysis and modelling of the uncertainty
3.4.2 Quantification of the power reserve
3.5 RISK-BASED UC FORMULATION
3.5.1 General scheme
3.5.2 UC objective function
3.5.3 UC constraints
3.5.4 MILP and DP methods for solving UC problems
3.6 PRESENTATION OF THE URBAN MICROGRID
3.7 GENERATION SCHEDULING WITH DP
3.7.1 Mathematical Formulation of the Dynamic Programming
3.7.2 N-1 criterion based deterministic optimization
3.7.3 Risk-based deterministic optimization
3.8 UNCERTAINTY PROPAGATION ANALYSIS WITH PROBABILISTIC METHODS
3.8.1 Characterization of PV forecast errors by confident intervals
3.8.2 Effect of PV uncertainty on the effective operating reserve
3.9 FROM DP TO MILP
3.9.1 Interests
3.9.2 Risk-based deterministic optimization with MILP
3.10 CONCLUSION
CHAPTER 4 ANTICIPATING UNCERTAINTY WITH A SCENARIO-BASED STOCHASTIC OPTIMIZATION
4.1 INTRODUCTION
4.2 NEEDS FOR UNCERTAINTIES MODELLING IN OPERATING PLANNING
4.2.1 Anticipating uncertainty with scenarios
4.2.2 From risk-based DUC to SUC
4.3 STOCHASTIC OPTIMIZATION METHODS FOR UC
4.3.1 State of the art
4.3.2 Issues and Contributions
4.4 SCENARIO-BASED STOCHASTIC OPTIMIZATION ALGORITHM
4.4.1 Scenario-based optimization methodology
4.4.2 First stage: Deterministic operational planning
4.4.3 Building of scenarios for the representation of uncertainty
4.4.4 Second stage: Stochastic operational planning
4.5 APPLICATION FOR THE OPERATIONAL PLANNING WITH THE SCENARIO-BASED STOCHASTIC OPTIMIZATION
4.5.1 Building of scenarios
4.5.2 Analysis of OR and generation scheduling
4.5.3 Impacts of the second stage optimization on the cost minimization
4.5.4 Impacts of the chosen risk criteria
4.5.5 Impacts of the RES self-production rate
4.6 CONCLUSION
CHAPTER 5 PARTICIPATION OF STORAGE FOR OPERATING RESERVE PROVISION 129
5.1 INTRODUCTION
5.2 OVERVIEW ON ENERGY STORAGE APPLICATIONS AND BENEFITS
5.2.1 Home energy storage
5.2.2 Renewable energy time-shift
5.2.3 Operating reserve supply
5.3 ENERGY STORAGE CONTROL STRATEGIES
5.3.1 Principle and framework
5.3.2 Storage control strategy for power balancing (strategy 1)
5.3.3 Storage control strategy for power reserve provision (strategy 2)
5.4 UC WITH A DETERMINISTIC OPTIMIZATION
5.4.1 Presentation
5.4.2 Objective function
5.4.3 Task and data of the study case
5.4.4 Applications results with the power balancing strategy (1)
5.4.5 Applications results with the OR provision strategy (2)
5.4.6 Comparison of the two control strategies and discussion
5.5 UC WITH A SCENARIO-BASED STOCHASTIC OPTIMIZATION
5.5.1 Presentation
5.5.2 Building of Net Demand scenarios for uncertainties representation
5.5.3 Stochastic Operational Planning with a Mixed-Integer Programming Optimization
5.5.4 Applications results with the power balancing strategy (1)
5.5.5 Applications results with the OR provision strategy (2)
5.5.6 Discussion about the two control strategies according to different uncertainties
5.6 SIZING OF STORAGE UNDER UNCERTAINTY
5.6.1 Principle
5.6.2 Load demand analysis
5.6.3 PV generation analysis
5.6.4 Expected net load demand
5.7 CONCLUSION
CHAPTER 6 MICROGIRD CENTRAL ENERGY MANAGEMENT SYSTEM INTERFACE DESIGN
6.1 INTRODUCTION
6.2 GUI DESCRIPTION
6.2.1 MCEMS functions presentation
6.2.2 Home interface window design
6.3 MAIN INTERFACES DESIGN
6.3.1 Data collection and predictive analysis for forecasting
6.3.2 System uncertainty assessment and OR quantification
6.3.3 Deterministic optimization for operational planning
6.3.4 Scenario-based stochastic optimization for operational planning
6.4 CONCLUSION
CHAPTER 7 GENERAL CONCLUSION AND PERSPECTIVES
APPENDIX 1. BACK-PROPAGATION NEURAL NETWORK
APPENDIX 2. STATISTICS AND PROBABILISTIC THEORIES
APPENDIX 3. BRANCH-AND-CUT ALGORITHM FOR MILP
RESUME ÉTENDU EN FRANÇAIS
REFERENCES
