(a) Forecasting

Forecasting is a process that uses past and present data for making predictions of future DERs, loads, and the market. Due to intermittency and variability of these factors, forecasting has become a challenging task for the power utilities. Therefore, accuracy of the forecast is crucial for the EMS to balance equality constraints, i.e., supply and demand in the microgrid. Various forecast methods are available in the literature:

• qualitative versus quantitative
• average approach
• drift
• time series
• causal/econometric
• judgmental
• artificial intelligence

(b) State Estimation

State estimation is a key function in building adequate network models for online monitoring and analyses. State estimation in a distribution system is becoming stringent because of the integration of DERs and the adoption of advanced technology for system modeling and operations for the distribution network. To manage large-scale DERs and load change, the operators in a distribution system need a robust distribution system state estimator (DSSE). The installation of supervisory control and data acquisition (SCADA) system at the feeder level and the widespread adoption of advanced metering infrastructure (AMI) have made the implementation of a reliable DSSE feasible. Various methods are utilized to solve DSSE issues, including:

• nonlinear model: [z] = [h(x)] + ϵ
• weighted least squares (WLS):
• solution based on normal equations

(c) Load Flow

Load-flow studies play an important role in power system analysis and design. They give the steady-state solution of a power system network for normal operating conditions, helping in continuous monitoring of the current state of the system, and are employed for planning, optimization, and stability studies. All distribution of electrical energy is done by a constant-voltage system. In practice, the following distribution circuits are generally used: radial system, ring main system (mesh system), and interconnected system. Distribution networks are characterized by radial structure with high (Resistance to Reactance Ratio) R/X ratio feeders.

A mesh network (having some loops) can be found in some modern distribution systems. A mesh network may be used to improve the system voltage profile, balance the load, and increase the supply reliability and efficiency. Thus, there is an increasing demand for a generalized load-flow method for distribution systems having more than one feeding source with a mesh-configured network. An efficient and fast load flow method is required. Load flow for a distribution system is divided into two categories:

• forward/backward sweep (FBS), ladder-network-based methods, and loop-impedance methods
• methods that require information on the derivatives of the network equations

(d) Real-Time Simulation

Real-time simulation refers to a simulation or computer model of a physical system that can execute at the same rate as actual “wall clock” time. For example:

• real-time means sixty seconds of simulation time equals sixty seconds
• offline means sixty seconds of simulation time can be five minutes, fifteen minutes, forty minutes, etc., depending on the network size being simulated

Various tools are available to work on real-time distribution systems, such as:

• real-time digital simulator (RTDS)
• real-time simulator (OPAL-RT technologies)
• DIgSILENT PowerFactory

For a deeper understanding, the reader can refer to papers on forecasting [18], state estimation [19], load flow [20], and real-time simulation of the microgrid [22].

14.2.1 Control Options for Microgrid Technology

Control options for a microgrid are as follows:

• Unit power control configuration tracks requests for power. If extra power is needed demands are made from the grid. Where heat is produced from the grid (p = f (H)) it is used for combined heat and power (CHP) applications.
• Feeder flow control configuration tracks requests for frequency, while extra demands for loads are provided by sources. Microgrids become a true dispatchable load as seen from the utility side, allowing for specific demand arrangements.
• Mixed control configuration allows some units to track power and others to track frequency. A unit can switch from one mode to another, allowing the system to operate at the most efficient capacity [4].

Branch-flow equation

 

(14.5)

where

(14.6)

Branch flow considers the recursive relationships between the successive nodes in the radial-distribution system. The demand in P, Q has an interruptible component, which is the load-management control option Y. In addition, the reactive power equation has the capacity-switching option Q_s.

Voltage limits/current limits:

(14.7)

(14.8)

Capacitor control limits:

(14.9)

Curtailable load-control limits:

(14.10)

(14.11)

Load Frequency Control

Load frequency control (LFC) is of importance in microgrid system design and operation. The objective of LFC in an interconnected power system is to maintain the frequency of each area within limits and to keep tie-line power flows within some prespecified tolerances by adjusting the megawatt (MW) outputs of the generators to accommodate fluctuating load demands. A well-designed and well-operated power system must cope with changes in the load and with system disturbances, and should provide an acceptably high level of power quality while maintaining both voltage and frequency within tolerance limits. As power load demand varies randomly for an interconnected power system, both area frequency and tie-line power interchange varies also. The primary objective of LFC is to minimize transient deviations in area frequency and tie-line power interchange while ensuring that steady-state errors are as close to zero as possible. Frequency will not change in an interconnected network if there is a balance between customer demand and power supply resources that can also compensate for electrical losses.

The operating point of the power system shifts from its scheduled operating point due to mismatch in generation and demand in the system. This is because without increase in mechanical input, sudden changes in demand in the system will be supplied from the stored kinetic energy of the rotating mass. This results a reduction in kinetic energy of the system, which will further cause the turbine speed reduction of the system. The speed is directly proportional to the frequency, hence frequency will also fail.

The incremental power in the generation and demand is expressed in the system as a change in kinetic energy, increased load consumption, and increased power transferred in the interconnected system. This relation between the incremental power and system dynamics is given as follows.

The stored energy in a generator rotor at the rated frequency and sensitive load dependency in frequency is

(14.12)

(14.13)

The incremental power is related to kinetic energy and frequency-dependent loads as shown:

(14.14)

Taking the Laplace transform of Equation 14.14,

(14.15)

(14.16)

(14.17)

where, ΔP_m and ΔP_L are the changes in mechanical power and load, Δf is the frequency deviation, H is the inertia constant, D is the load-damping coefficient, K_P is the power system gain given by K_P = 1/D, and T_P is the power system time constant .

The aim is to minimize frequency deviation (ΔF) due to mismatch between generation and load.

14.2.2 Demand Response

Practically speaking, electrical power cannot be easily stored on a large scale. Thus, supply and demand must remain in balance in real time. Traditionally, utility companies have leveraged peaking power plants to increase power generation when needed to meet demand. Demand response, however, works from the opposite side of the equation: instead of adding more generation to the system, it pays energy users to reduce their consumption. Utilities pay for demand-response capacity because it is proven to be more flexible and less expensive than bringing additional generation online.

Demand response offers an opportunity for consumers to play a substantial role in the operation of the microgrid by decreasing or shifting their electricity use during peak periods in response to time-based rates or other financial incentives. Demand-response programs are being utilized by electric system planners and operators as resource options for balancing supply and demand. These programs aid in lowering the cost of electricity in wholesale markets, which in turn leads to lower retail rates.

Techniques of engaging customers in demand-response efforts include offering time-based rates such as critical peak pricing, variable peak pricing, time-of-use pricing, critical peak rebates, and real-time pricing. Other techniques include direct load-control programs that provide the ability for power utility companies to cycle loads that are noncritical, such as water heaters and air conditioners, on and off during periods of peak demand in return for a financial incentive and lower electricity bills.

Demand-response programs are becoming an increasingly valuable resource option whose capabilities and potential impacts are expanded by modern microgrids. Microgrids have numerous sensors that can distinguish peak load problems and utilize automatic switching to divert or decrease power in strategic places, which removes the chance of overload and a resulting power failure. Advanced metering infrastructure increases the range of time-based rate programs that may be offered to consumers and smart customer systems such as in-home displays or home-area-networks that make it easier for consumers to change their electricity consumption patterns and reduce peak-period consumption based on information on their power consumption and costs. These programs also possess the potential to assist electricity providers in saving money through reductions in system peak demand, and the ability to defer addition or construction of new DG plants and power-delivery systems—particularly those reserved for use during peak times.

14.2.3 Demand-Side Management

Demand-side management (DSM) is a set of interconnected and flexible programs that allow customers a bigger role in shifting their own demand for electricity during peak periods, reducing their energy consumption overall. DSM program consists of two principal activities: demand response programs or “load shifting,” and energy efficiency and conservation.

The evolution of microgrid technology will permit customers to make informed decisions about their energy consumption, regulating both its timing and quantity.

Key levers of successful DSM initiatives include incentives, rates, technology, access to information, controls, public education, and marketing, along with verification and customer insight. Each lever has a distinct influence on customer behavior and depends on the circumstances of the particular utility, such as customer base and geography. Certain combinations of actions within and across levels may produce greater results.

14.2.4 Reconfiguration

In an emergency, a microgrid is frequently required to reconfigure itself as soon as possible in order to support continuous electricity supply to essential loads. Types of operations, including topology switching, generation regulation, and load shedding, are concerned with reconfiguration. Therefore, the problem of reconfiguration turns out to be a typical constrained, nonlinear optimization problem with discrete, Boolean and continuous variables, which is usually too complex to be solved by regular optimization methods. Reconfiguration is a category of emergency control, which includes topology changes with load-generation control measures that play an essential role in helping microgrids switch from integration mode to island mode.

Dissimilar from large systems, topology reconfiguration is deemed as the final line of defense, only taken into consideration when there is an extreme emergency state to avoid uncontrollable blackout of the entire system—while it is a frequently used control method in microgrids. In an emergency, the microgrid is expected to be operated as an island to protect itself from being infected by faults in the main system. By applying flexible electrical/electronic interfaces, both microgrid and energy storage systems can switch on/off seamlessly and realize “plug and play” functionality.

14.2.5 Fault Analysis

Generally, a microgrid can operate in both the grid-connected mode and the islanded mode, where the microgrid interfaces with the main power system by a fast semiconductor switch called a static switch (SS). It is critical to protect a microgrid in both the grid-connected and the islanded modes of operation against all types of faults. The major problem arises in island operation with inverter-based sources. Inverter fault currents are limited by the ratings of the silicon devices to around two per unit rated current. Fault currents in islanded inverter-based microgrids may not have sufficient magnitudes to use traditional over-current protection systems. This possibility requires an extended protection strategy. The philosophy for protection is to have the same protection strategies for both islanded and grid-connected operation. The SS is designed to open for all faults. With the SS open, faults within the microgrid must be cleared with techniques that do not rely on high-fault currents. The fault analysis of a power system is required in order to provide information for the setting of relays, selection of switchgear, and stability of system operation. Several types of fault analysis are carried out using software packages and data collected from the microgrid system. Faulty-analysis types include symmetrical and asymmetrical, short circuit, stability, and transient.

14.2.6 Energy Pricing

Microgrid is a concept where local energy sources in remote areas, both in renewable (such as PV, small wind generator, etc.) and nonconventional (fuel cells, microturbine, and diesel generator) resources, are tapped and interconnected to form a low-voltage utility system. These small DGs all have different owners, and the supply loads locally with the help of local controllers (µc). A µC controller takes decisions such as scheduling of generation as per load forecast (i.e., unit commitment) and economic dispatch of connection with each DG and microgrid central controller (µcc). In the islanding operation of a microgrid, each source caters to only those loads stipulated for the source. However, when these sources are connected with the microgrid, which is most desirable, the action of the controllers should have a certain degree of intelligence for participation in a common and competitive market. The role of the EMS in the microgrid scenario is for making decisions with regard to the best use of the generator for producing heat and electricity, i.e., CHP operation. Such decisions are based upon the heat requirements of the local establishments, climate, cost of fuel, price of electric power, and many other variables.

The market price is the lowest price obtained at the point of intersection of the aggregated supply and demand curves. At this price both suppliers of generation and customers are satisfied and enough electricity will be supplied from accepted sales bids to satisfy all the accepted purchase bids. The costs incurred in the production of electricity are solely dependent on the type of technologies and fuel used for electricity production. The DG units that use natural gas (microturbines) or diesel have higher marginal costs and these plants are called the price setting units, while mini-hydro plants have a low marginal cost. Electricity cannot be stored as long as there are no electricity alternatives for consumers to react to the price signal. These two points lead to an inelastic demand curve.

In the case of renewable sources, the current cost of buying energy is relatively low, with no fuel or operational costs involved compared to the capital cost of buying a wind turbine or PV module. Economic analyses in these cases are performed using a simple payback period. CO₂ emissions are absent and the resulting no-carbon incentives are an added advantage. Since electricity can be produced in many ways using a variety of fuels and applying different technologies, different cost structures apply, with important implications for price formation on short-term electricity markets.

14.3.1 IEEE Standards for Synchro Phasors for Power Systems (IEEE C37.118, 2005)

This standard defines synchronized phasor measurements used in power system applications. It provides a method to quantify the measurement, tests to be sure the measurement conforms to the definition, and error limits for the test. It also defines a data communication protocol, including message formats for communicating this data in a real-time system.

14.3.2 IEEE Standard for Interconnecting Distributed Resources with the Electric Power System (IEEE 1547, 2003)

This standard focuses on the technical specifications for, and testing of, the interconnection itself. It provides requirements relevant to the performance, operation, testing, safety considerations, and maintenance of the interconnection. It includes general requirements, response to abnormal conditions, PQ, islanding, and test specifications and requirements for design, production, installation evaluation, commissioning, and periodic tests. The stated requirements are universally needed for interconnection of distributed resources (DR), including synchronous machines, induction machines, and power inverters/converters, and will be sufficient for most installations. The criteria and requirements are applicable to all DR technologies with aggregate capacity of 10MVA or less at the point of common coupling, interconnected to electric power systems at typical primary and/or secondary distribution voltages. Installation of DR on radial primary and secondary distribution systems is the main emphasis of this standard, although installation of DR on primary and secondary network distribution systems is also considered. This standard is written considering that the DR is a 60 Hz source.

14.3.3 Common Information Model for Power Systems (IEC 61968/61970)

The IEC 61970 series of standards deals with the application program interfaces for EMS. The series provides a set of guidelines and standards to facilitate:

• integration of applications developed by different suppliers in the control center environment
• exchange of information to systems external to the control center environment, including transmission, distribution, and generation systems external to the control center that need to exchange real-time data with the control center
• provision of suitable interfaces for data exchange across legacy and new systems

14.3.4 Communication Networks and Systems in Substations (IEC 61850, Ed. 1, 2009)

High-speed peer-to-peer IEC 61850-8-1 (International Electrotechnical Commission (IEC) 61850-8-1) generic-object-oriented substation event (GOOSE) and IEC 61850-9-2 sampled values (SVs)–based information exchange among IEDs in modern IEC 61850 substations have opened the opportunity for designing and developing innovative all-digital protection applications. The transmission reliability and real-time performance of SVs and GOOSE messages, over the process-bus network, are critical to realize all-digital IEC 61850 substation automation systems (SASs) protection applications. To address the reliability, availability, and deterministic delay performance needs of SASs, a novel IEC 61850-9-2 process-bus based substation communication network (SCN) architecture is proposed in this standard.

14.3.5 Advanced Metering Infrastructure System Security Requirements (AMI–SEC, June 2009)

This standard provides the utility industry and vendors with a set of security requirements for advanced metering infrastructure (AMI) to be used in the procurement process, and represents a superset of requirements gathered from current cross-industry-accepted security standards and best practice guidance documents.

14.3.6 American National Standards Institute (ANSI) End-Device Data Tables (ANSI C12.19, 2008)

This standard defines a table structure for utility application data to be passed between an end device and a computer. The end device is typically an electricity meter, and the computer is typically a handheld device carried by a meter reader, or a meter communication module that is part of an automatic meter-reading system. C12.19 does not define end-device design criteria or specify the language or protocol used to transport that data. There are however related ANSI standards that do specify the transportation of these tables. ANSI C12.18 describes the communication of C12.19 tables over an optical port. ANSI C12.21 describes the communication of C12.19 tables over a modem. ANSI C12.22 describes the communication of C12.19 tables over a network.

14.4.1 Cost–Benefit Analysis in Microgrids

• Distribution automation has been a promising area of development in support of distribution systems.
• The potential benefits and costs associated with these functions are quantifiable.
• Research has been carried out to determine the costs and benefits to justify the feasibility of undertaking the automation of distribution system networks.
• Benefits to customers may not be obvious or justifiable based on the existing technology and the present costs associated with it.

14.4.2 Cost–Benefit Analysis Methodology

The revenue-requirements model is the most rigorous methodology for electric utility cost–benefit analysis. This technique represents the complete financial environment of a utility, accounting for taxes, depreciation, and time/value costs of money, actual capital investment, and operation and maintenance expenses. Two or more alternatives, each of which may involve differing life cycles and cash flows, can be compared on a common basis. With the revenue-requirement methodology, several alternatives are defined, and the cash flows for capital investment and operation and maintenance expenses are determined.

14.4.3 Illustrative Problems and Examples